hh.sePublikationer
Ändra sökning
Avgränsa sökresultatet
123456 101 - 150 av 269
RefereraExporteraLänk till träfflistan
Permanent länk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Träffar per sida
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sortering
  • Standard (Relevans)
  • Författare A-Ö
  • Författare Ö-A
  • Titel A-Ö
  • Titel Ö-A
  • Publikationstyp A-Ö
  • Publikationstyp Ö-A
  • Äldst först
  • Nyast först
  • Skapad (Äldst först)
  • Skapad (Nyast först)
  • Senast uppdaterad (Äldst först)
  • Senast uppdaterad (Nyast först)
  • Disputationsdatum (tidigaste först)
  • Disputationsdatum (senaste först)
  • Standard (Relevans)
  • Författare A-Ö
  • Författare Ö-A
  • Titel A-Ö
  • Titel Ö-A
  • Publikationstyp A-Ö
  • Publikationstyp Ö-A
  • Äldst först
  • Nyast först
  • Skapad (Äldst först)
  • Skapad (Nyast först)
  • Senast uppdaterad (Äldst först)
  • Senast uppdaterad (Nyast först)
  • Disputationsdatum (tidigaste först)
  • Disputationsdatum (senaste först)
Markera
Maxantalet träffar du kan exportera från sökgränssnittet är 250. Vid större uttag använd dig av utsökningar.
  • 101.
    Fernandez-de-Sevilla, R.
    et al.
    Universidad Autonoma de Madrid, Spain.
    Alonso-Fernandez, Fernando
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Fierrez, J.
    Universidad Autonoma de Madrid, Spain.
    Ortega-Garcia, J.
    Universidad Autonoma de Madrid, Spain.
    Forensic Writer Identification Using Allographic Features2010Ingår i: Proceedings: 12th International Conference on Frontiers in Handwriting Recognition, ICFHR 2010, Los Alamitos, Calif.: IEEE Computer Society, 2010, s. 308-313Konferensbidrag (Refereegranskat)
    Abstract [en]

    Questioned document examination is extensively used by forensic specialists for criminal identification. This paper presents a writer recognition system based on allographic features operating in identification mode (one-to-many). It works at the level of isolated characters, considering that each writer uses a reduced number of shapes for each one. Individual characters of a writer are manually segmented and labeled by an expert as pertaining to one of 62 alphanumeric classes (10 numbers and 52 letters, including lowercase and uppercase letters), being the particular setup used by the forensic laboratory participating in this work. A codebook of shapes is then generated by clustering and the probability distribution function of allograph usage is the discriminative feature used for recognition. Results obtained on a database of 30 writers from real forensic documents show that the character class information given by the manual analysis provides a valuable source of improvement, justifying the proposed approach. We also evaluate the selection of different alphanumeric channels, showing a dependence between the size of the hit list and the number of channels needed for optimal performance. © 2010 IEEE.

    Ladda ner fulltext (pdf)
    fulltext
  • 102.
    Fierrez, Julian
    et al.
    Universidad Autonoma de Madrid, Spain.
    Galbally, Javier
    Universidad Autonoma de Madrid, Spain.
    Ortega-Garcia, Javier
    Universidad Autonoma de Madrid, Spain.
    Freire, Manuel R.
    Universidad Autonoma de Madrid, Spain.
    Alonso-Fernandez, Fernando
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Ramos, Daniel R.
    Universidad Autonoma de Madrid, Spain.
    Toledano, Doroteo Torre
    Universidad Autonoma de Madrid, Spain.
    Gonzalez-Rodriguez, Joaquin
    Universidad Autonoma de Madrid, Spain.
    Siguenza, Juan A.
    Universidad Autonoma de Madrid, Spain.
    Garrido-Salas, Javier
    Universidad Autonoma de Madrid, Spain.
    Anguiano-Rey, Eloy
    Universidad Autonoma de Madrid, Spain.
    Gonzalez-de-Rivera, Guillermo
    Universidad Autonoma de Madrid, Spain.
    Ribalda, Ricardo
    Universidad Autonoma de Madrid, Spain.
    Faundez-Zanuy, Marcos
    Escuela Universitaria Politecnica de Mataro, Avda. Puig i Cadafalch 101-111, 08303 Mataro, Barcelona, Spain.
    Ortega, Juan Antonio Rosell
    Universidad Politecnica de Cataluña, Esc. Univ. de Ing. Tec. Ind. de Terrassa, C/ Colom 1, 08222 Terrassa, Barcelona, Spain.
    Cardenoso-Payo, Valentín
    Universidad de Valladolid, Edif. de Tecnicas de la Inf. y las Telecom., Campus Miguel, 47011 Valladolid, Spain.
    Viloria, A.
    Universidad de Valladolid, Edif. de Tecnicas de la Inf. y las Telecom., Campus Miguel, 47011 Valladolid, Spain.
    Vivaracho, Carlos E.
    Universidad de Valladolid, Edif. de Tecnicas de la Inf. y las Telecom., Campus Miguel, 47011 Valladolid, Spain.
    Moro, Q. Isaac
    Universidad de Valladolid, Edif. de Tecnicas de la Inf. y las Telecom., Campus Miguel, 47011 Valladolid, Spain.
    Igarza, Juan J.
    Escuela Superior de Ingenieros, Universidad del Pais Vasco, C/ Alameda de Urquijo s/n, 48013 Bilbao, Spain.
    Sanchez, Jon I.
    Escuela Superior de Ingenieros, Universidad del Pais Vasco, C/ Alameda de Urquijo s/n, 48013 Bilbao, Spain.
    Hernaez, Inmaculada
    Escuela Superior de Ingenieros, Universidad del Pais Vasco, C/ Alameda de Urquijo s/n, 48013 Bilbao, Spain.
    Orrite-Urunuela, Carlos
    Computer Vision Laboratory Group, Universidad de Zaragoza, Edif. Ada Byron, C/ Maria de Luna 1, 50018 Zaragoza, Spain.
    Martinez-Contreras, Francisco
    Computer Vision Laboratory Group, Universidad de Zaragoza, Edif. Ada Byron, C/ Maria de Luna 1, 50018 Zaragoza, Spain.
    Gracia-Roche, Juan José
    Computer Vision Laboratory Group, Universidad de Zaragoza, Edif. Ada Byron, C/ Maria de Luna 1, 50018 Zaragoza, Spain.
    BiosecurID: A Multimodal Biometric Database2010Ingår i: Pattern Analysis and Applications, ISSN 1433-7541, E-ISSN 1433-755X, Vol. 13, nr 2, s. 235-246Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A new multimodal biometric database, acquired in the framework of the BiosecurID project, is presented together with the description of the acquisition setup and protocol. The database includes eight unimodal biometric traits, namely: speech, iris, face (still images, videos of talking faces), handwritten signature and handwritten text (on-line dynamic signals, off-line scanned images), fingerprints (acquired with two different sensors), hand (palmprint, contour-geometry) and keystroking. The database comprises 400 subjects and presents features such as: realistic acquisition scenario, balanced gender and population distributions, availability of information about particular demographic groups (age, gender, handedness), acquisition of replay attacks for speech and keystroking, skilled forgeries for signatures, and compatibility with other existing databases. All these characteristics make it very useful in research and development of unimodal and multimodal biometric systems. © Springer-Verlag London Limited 2009.

    Ladda ner fulltext (pdf)
    fulltext
  • 103.
    Fierrez, Julian
    et al.
    Universidad Autonoma de Madrid, Madrid, Spain.
    Li, Stan Z.Chinese Academy of Sciences, Beijing, China.Ross, ArunMichigan State University, East Lansing, USA.Veldhuis, RaymondUniversity of Twente, Enschede, Netherlands.Alonso-Fernandez, FernandoHögskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).Bigun, JosefHögskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    2016 International Conference on Biometrics (ICB): Proceedings: 13-16 June 2016, Halmstad, Sweden2016Proceedings (redaktörskap) (Refereegranskat)
  • 104.
    Fierrez-Aguilar, J.
    et al.
    Universidad Autonoma de Madrid, Spain.
    Munoz-Serrano, L. M.
    Universidad Autonoma de Madrid, Spain.
    Alonso-Fernandez, Fernando
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Ortega-Garcia, J.
    Universidad Autonoma de Madrid, Spain.
    On the effects of image quality degradation on minutiae- and ridge-based automatic fingerprint recognition2005Ingår i: Proceedings: International Carnahan Conference on Security Technology, Piscataway, N.J.: IEEE Press, 2005, s. 79-82Konferensbidrag (Refereegranskat)
    Abstract [en]

    The effect of image quality degradation on the verification performance of automatic fingerprint recognition is investigated. We study the performance of two fingerprint matchers based on minutiae and ridge information under varying fingerprint image quality. The ridge-based system is found to be more robust to image quality degradation than the minutiae-based system for a number of different image quality criteria. © 2005 IEEE.

    Ladda ner fulltext (pdf)
    fulltext
  • 105.
    Fierrez-Aguilar, Julian
    et al.
    Universidad Politecnica de Madrid, Madrid, Spain.
    Ortega-Garcia, J.
    Universidad Politecnica de Madrid, Madrid, Spain.
    Gonzalez-Rodrigueza, J.
    Universidad Politecnica de Madrid, Madrid, Spain.
    Bigun, Josef
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Kernel-based multimodal biometric verification using quality signals2004Ingår i: Proceedings of SPIE: Biometric Technology for Human Identification / [ed] Anil K. Jain, Nalini K. Ratha, 2004, Vol. 5404, s. 544-554Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    A novel kernel-based fusion strategy is presented. It is based on SVM classifiers, trade-off coefficients introduced in the standard SVM training and testing procedures, and quality measures of the input biometric signals. Experimental results on a prototype application based on voice and fingerprint traits are reported. The benefits of using the two modalities as compared to only using one of them are revealed. This is achieved by using a novel experimental procedure in which multi-modal verification performance tests are compared with multi-probe tests of the individual subsystems. Appropriate selection of the parameters of the proposed quality-based scheme leads to a quality-based fusion scheme outperforming the raw fusion strategy without considering quality signals. In particular, a relative improvement of 18% is obtained for small SVM training set size by using only fingerprint quality labels.

  • 106. Flys, Olena
    et al.
    Berglund, J.
    RISE Research Institutes of Sweden, Borås, Sweden | Department of Industrial and Materials Science, Chalmers University of Technology, Gothenburg, Sweden.
    Rosén, Bengt Göran
    Högskolan i Halmstad, Akademin för företagande, innovation och hållbarhet, Rydberglaboratoriet för tillämpad naturvetenskap (RLAS).
    Using confocal fusion for measurement of metal AM surface texture2020Ingår i: Surface Topography: Metrology and Properties, ISSN 2051-672X, Vol. 8, nr 2, artikel-id 024003Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The highly complex nature of as printed metal AM surfaces pose other challenges for making measurements compared to surfaces made with many conventional processing methods. The high complexity is caused by high aspect ratios, a mix of high and low reflexivity, steep angles etc. It is not clear which method is the most suitable for measuring these surfaces. The objective of this study was to compare four different measurement modes available in one instrument to evaluate the advantages and drawbacks of the respective techniques regarding measurements of metal AM surfaces. The evaluated measurement modes are Confocal Microscopy, Coherence Scanning Interferometry, Focus Variation and Confocal Fusion. The effect of advantages and drawbacks of studied techniques was tested on typical surfaces produced by L-PBF process. Surfaces printed at 0° and 90° inclinations were compared regarding the measurement results achieved from the different methods. The Power Spectral Density analysis and visual comparison were used for the examination of studied measurements methods. Besides the comparison of areal measurements acquired by different modes available in the instrument also extracted profile measurements were compared with profile images acquired using an Optical Microscope. This study reveals that confocal fusion is a promising technique for AM surface characterisation, due to the highest amount of valid data points in the typical measurement. The new approach developed in the study showed that PSD analysis can be used for evaluation of fill in algorithms incorporated in different software. Results of the profile comparisons help to illustrate features that can be depicted by surface measurements, applying different measurement principles, as well as enables comparison of raw profile data between different types of measurements. Further investigation of measurements on AM surfaces in the frequency domain will bring more understanding about the limitations of measurement techniques. © 2020 IOP Publishing Ltd.

  • 107.
    Galbally, J.
    et al.
    Universidad Autonoma de Madrid, Spain.
    Alonso-Fernandez, Fernando
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Fierrez-Aguilar, J.
    Universidad Autonoma de Madrid, Spain.
    Ortega-Garcia, J.
    Universidad Autonoma de Madrid, Spain.
    Fingerprint Liveness Detection Based on Quality Measures2009Ingår i: 2009 1st IEEE International Conference on Biometrics, Identity and Security, BIdS 2009, Piscataway, N.J.: IEEE Press, 2009, s. 1-8Konferensbidrag (Refereegranskat)
    Abstract [en]

    A new fingerprint parameterization for liveness detection based on quality measures is presented. The novel feature set is used in a complete liveness detection system and tested on the development set of the LivDET competition, comprising over 4,500 real and fake images acquired with three ditTerent optical sensors. The proposed solution proves to be robust to the multi-sensor scenario, and presents an overall rate of 93% of correctly classified samples. Furthermore, the liveness detection method presented has the added advantage over previously studied techniques of needing just one image from a finger to decide whether it is real or fake.

    Ladda ner fulltext (pdf)
    fulltext
  • 108.
    Galbally, Javier
    et al.
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Alonso-Fernandez, Fernando
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Fierrez, Julian
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Ortega-Garcia, Javier
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    A High Performance Fingerprint Liveness Detection Method Based on Quality Related Features2012Ingår i: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 28, nr 1, s. 311-321Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A new software-based liveness detection approach using a novel fingerprint parameterization based on quality related features is proposed. The system is tested on a highly challenging database comprising over 10,500 real and fake images acquired with five sensors of different technologies and covering a wide range of direct attack scenarios in terms of materials and procedures followed to generate the gummy fingers. The proposed solution proves to be robust to the multi-scenario dataset, and presents an overall rate of 90% correctly classified samples. Furthermore, the liveness detection method presented has the added advantage over previously studied techniques of needing just one image from a finger to decide whether it is real or fake. This last characteristic provides the method with very valuable features as it makes it less intrusive, more user friendly, faster and reduces its implementation costs. © 2010 Elsevier B.V. All rights reserved.

    Ladda ner fulltext (pdf)
    fulltext
  • 109.
    Galbally, Javier
    et al.
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Fierrez, Julian
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Alonso-Fernandez, Fernando
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Martinez-Diaz, Marcos
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Evaluation of Direct Attacks to Fingerprint Verification Systems2011Ingår i: Telecommunications Systems, ISSN 1018-4864, E-ISSN 1572-9451, Vol. 47, nr 3, s. 243-254Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The vulnerabilities of fingerprint-based recognition systems to direct attacks with and without the cooperation of the user are studied. Two different systems, one minutiae-based and one ridge feature-based, are evaluated on a database of real and fake fingerprints. Based on the fingerprint images quality and on the results achieved on different operational scenarios, we obtain a number of statistically significant observations regarding the robustness of the systems. © 2010 Springer Science+Business Media, LLC.

  • 110.
    Galbally-Herrero, J.
    et al.
    Universidad Autonoma de Madrid, Spain.
    Fierrez-Aguilar, J.
    Universidad Autonoma de Madrid, Spain.
    Rodriguez-Gonzalez, J. D.
    Universidad Autonoma de Madrid, Spain.
    Alonso-Fernandez, Fernando
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Ortega-Garcia, J.
    Universidad Autonoma de Madrid, Spain.
    Tapiador, M.
    Universidad Autonoma de Madrid, Spain.
    On the vulnerability of fingerprint verification systems to fake fingerprint attacks2006Ingår i: Proceedings: International Carnahan Conference on Security Technology, Piscataway, N.J.: IEEE Press, 2006, s. 130-136Konferensbidrag (Refereegranskat)
    Abstract [en]

    A new method to generate gummy fingers is presented. A medium-size fake fingerprint database is described and two different fingerprint verification systems are evaluated on it. Three different scenarios are considered in the experiments, namely: enrollment and test with real fingerprints, enrollment and test with fake fingerprints, and enrollment with real fingerprints and test with fake fingerprints. Results for an optical and a thermal sweeping sensors are given. Both systems are shown to be vulnerable to direct attacks. © 2006 IEEE.

    Ladda ner fulltext (pdf)
    fulltext
  • 111.
    Galozy, Alexander
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Data-driven personalized healthcare: Towards personalized interventions via reinforcement learning for Mobile Health2021Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    Medical and technological advancement in the last century has led to the unprecedented increase of the populace's quality of life and lifespan. As a result, an ever-increasing number of people live with chronic health conditions that require long-term treatment, resulting in increased healthcare costs and managerial burden to the healthcare provider. This increase in complexity can lead to ineffective decision-making and reduce care quality for the individual while increasing costs. One promising direction to tackle these issues is the active involvement of the patient in managing their care. Particularly for chronic diseases, where ongoing support is often required, patients must understand their illness and be empowered to manage their care. With the advent of smart devices such as smartphones, it is easier than ever to provide personalised digital interventions to patients, help them manage their treatment in their daily lives, and raise awareness about their illness. If such new approaches are to succeed, scalability is necessary, and solutions are needed that can act autonomously without costly human intervention. Furthermore, solutions should exhibit adaptability to the changing circumstances of an individual patient's health, needs and goals. Through the ongoing digitisation of healthcare, we are presented with the unique opportunity to develop cost-effective and scalable solutions through Artificial Intelligence (AI).

    This thesis presents work that we conducted as part of the project improving Medication Adherence through Person-Centered Care and Adaptive Interventions (iMedA) that aims to provide personalised adaptive interventions to hypertensive patients, supporting them in managing their medication regiment. The focus lies on inadequate medication adherence (MA), a pervasive issue where patients do not take their medication as instructed by their physician. The selection of individuals for intervention through secondary database analysis on Electronic Health Records (EHRs) was a key challenge and is addressed through in-depth analysis of common adherence measures, development of prediction models for MA and discussions on limitations of such approaches for analysing MA. Furthermore, providing personalised adaptive interventions is framed in the contextual bandit setting and addresses the challenge of delivering relevant interventions in environments where contextual information is significantly corrupted.       

    The contributions of the thesis can be summarised as follows: (1) Highlighting the issues encountered in measuring MA through secondary database analysis and providing recommendations to address these issues, (2) Investigating machine learning models developed using EHRs for MA prediction and extraction of common refilling patterns through EHRs and (3) formal problem definition for a novel contextual bandit setting with context uncertainty commonly encountered in Mobile Health and development of an algorithm designed for such environments.  

    Ladda ner fulltext (pdf)
    fulltext
  • 112.
    Galozy, Alexander
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Nowaczyk, Sławomir
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Prediction and pattern analysis of medication refill adherence through electronic health records and dispensation data2020Ingår i: Journal of Biomedical Informatics: X, E-ISSN 2590-177X, Vol. 6-7, artikel-id 100075Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Background and purpose

    Low adherence to medication in chronic disease patients leads to increased morbidity, mortality, and healthcare costs. The widespread adoption of electronic prescription and dispensation records allows a more comprehensive overview of medication utilization. In combination with electronic health records (EHR), such data provides new opportunities for identifying patients at risk of nonadherence and provide more targeted and effective interventions. The purpose of this article is to study the predictability of medication adherence for a cohort of hypertensive patients, focusing on healthcare utilization factors under various predictive scenarios. Furthermore, we discover common proportion of days covered patterns (PDC-patterns) for patients with index prescriptions and simulate medication-taking behaviours that might explain observed patterns.

    Procedures

    We predict refill adherence focusing on factors of healthcare utilization, such as visits, prescription information and demographics of patient and prescriber. We train models with machine learning algorithms, using four different data splits: stratified random, patient, temporal forward prediction with and without index patients. We extract frequent, two-year long PDC-patterns using K-means clustering and investigate five simple models of medication-taking that can generate such PDC-patterns.

    Findings

    Model performance varies between data splits (AUC test set: 0.77–0.89). Including historical information increases the performance slightly in most cases (approx. 1–2% absolute AUC uplift). Models show low predictive performance (AUC test set: 0.56–0.66) on index-prescriptions and patients with sudden drops in PDC (Recall: 0.58–0.63). We find 21 distinct two-year PDC-patterns, ranging from good adherence to intermittent gaps and early discontinuation in the first or second year. Simulations show that observed PDC-patterns can only be explained by specific medication consumption behaviours.

    Conclusions

    Prediction models developed using EHR exhibit bias towards patients with high healthcare utilization. Even though actual medication-taking is not observable, consumption patterns may not be as arbitrary, provided that medication refilling and consumption is linked.  © 2020 The Authors. Published by Elsevier Inc.

  • 113.
    Gangwar, Abhishek
    et al.
    Centre for Development of Advanced Computing (CDAC), Mumbai, India.
    Joshi, Akanksha
    Centre for Development of Advanced Computing (CDAC), Mumbai, India.
    Singh, Ashutosh
    Centre for Development of Advanced Computing (CDAC), Mumbai, India.
    Alonso-Fernandez, Fernando
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Bigun, Josef
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    IrisSeg: A Fast and Robust Iris Segmentation Framework for Non-Ideal Iris Images2016Ingår i: 2016 INTERNATIONAL CONFERENCE ON BIOMETRICS (ICB) / [ed] J. Fierrez, S.Z. Li, A. Ross, R. Veldhuis, F. Alonso-Fernandez, J. Bigun, Piscataway: IEEE, 2016Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper presents a state-of-the-art iris segmentation framework specifically for non-ideal irises. The framework adopts coarse-to-fine strategy to localize different boundaries. In the approach, pupil is coarsely detected using an iterative search method exploiting dynamic thresholding and multiple local cues. The limbic boundary is first approximated in polar space using adaptive filters and then refined in Cartesianspace. The framework is quite robust and unlike the previously reported works, does notrequire tuning of parameters for different databases. The segmentation accuracy (SA) is evaluated using well known measures; precision, recall and F-measure, using the publicly available ground truth data for challenging iris databases; CASIAV4-Interval, ND-IRIS-0405, and IITD. In addition, the approach is also evaluated on highly challenging periocular images of FOCS database. The validity of proposed framework is also ascertained by providing comprehensive comparisons with classical approaches as well asstate-of-the-art methods such as; CAHT, WAHET, IFFP, GST and Osiris v4.1. The results demonstrate that our approach provides significant improvements in segmentation accuracy as well as in recognition performance that too with lower computational complexity. © 2016 IEEE.

    Ladda ner fulltext (pdf)
    fulltext
  • 114.
    Garcia-Salicetti, S.
    et al.
    Institut National des Tëlëcommunications, France.
    Fierrez-Aguilar, J.
    Universidad Autonoma de Madrid, Spain.
    Alonso-Fernandez, Fernando
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Vielhauer, C.
    Otto-Von-Guericke University of Magdeburg, Germany.
    Guest, R.
    University of Kent, Canterbur, United Kingdom.
    Allano, L.
    Institut National des Tëlëcommunications, France.
    Trung, T. Doan
    Institut National des Tëlëcommunications, France.
    Scheidat, T.
    Otto-Von-Guericke University of Magdeburg, Germany.
    Van, B. Ly
    Institut National des Tëlëcommunications, France.
    Dittmann, J.
    Otto-Von-Guericke University of Magdeburg, Germany.
    Dorizzi, B.
    Institut National des Tëlëcommunications, France.
    Ortega-Garcia, J.
    Universidad Autonoma de Madrid, Spain.
    Gonzalez-Rodriguez, J.
    Universidad Autonoma de Madrid, Spain.
    Castiglione, M. Bacile di
    University of Kent, Canterbur, United Kingdom.
    Fairhurst, M.
    University of Kent, Canterbur, United Kingdom.
    Biosecure reference systems for on-line signature verification: A study of complementarity2007Ingår i: Annales des télécommunications, ISSN 0003-4347, E-ISSN 1958-9395, Vol. 62, nr 1-2, s. 36-61Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In this paper, we present an integrated research study in On-line Signature Verification undertaken by several teams that participate in the BioSecure Network of Excellence. This integrated work, started during the First BioSecure Residential Workshop, has as main objective the development of an On-line Signature Verification evaluation platform. As a first step, four On-line Signature Verification Systems based on different approaches are evaluated and compared following the same experimental protocol on MCYT signature database, which is the largest existing on-line western signature database publicly available with 16 500 signatures from 330 clients. A particular focus of work documented in this paper is multi-algorithmic fusion in order to study the complementarity of the approaches involved. To this end, a simple fusion method based on the Mean Rule is used after a normalization phase.

    Ladda ner fulltext (pdf)
    fulltext
  • 115.
    Garcia-Salicetti, S.
    et al.
    TELECOM SudParis (ex GET-INT), 9, rue Charles Fourier, 91011, Evry, France .
    Houmani, N.
    TELECOM SudParis (ex GET-INT), 9, rue Charles Fourier, 91011, Evry, France .
    Ly-Van, B.
    TELECOM SudParis (ex GET-INT), 9, rue Charles Fourier, 91011, Evry, France .
    Dorizzi, B.
    TELECOM SudParis (ex GET-INT), 9, rue Charles Fourier, 91011, Evry, France .
    Alonso-Fernandez, Fernando
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Fierrez, J.
    Univ. Autonoma de Madrid, Spain.
    Ortega-Garcia, J.
    Univ. Autonoma de Madrid, Spain.
    Vielhauer, C.
    Univ. Autonoma de Madrid, Spain.
    Scheidat, T.
    Univ. Autonoma de Madrid, Spain.
    Online Handwritten Signature Verification2009Ingår i: Guide to Biometric Reference Systems and Performance Evaluation / [ed] Petrovska-Delacretaz, D.; Chollet, G.; Dorizzi, B., London: Springer London, 2009, s. 125-165Kapitel i bok, del av antologi (Övrigt vetenskapligt)
    Abstract [en]

    In this chapter, we first provide an overview of the existing main approaches, databases, evaluation campaigns and the remaining challenges in online handwritten signature verification. We then propose a new benchmarking framework for online signature verification by introducing the concepts of “Reference Systems”, “Reference Databases” and associated “Reference Protocols.” Finally, we present the results of several approaches within the proposed evaluation framework. Among them are also present the best approaches within the first international Signature Verification Competition held in 2004 (SVC’2004), Dynamic Time Warping and Hidden Markov Models. All these systems are evaluated first within the benchmarking framework and also with other relevant protocols. Experiments are also reported on two different databases (BIOMET and MCYT) showing the impact of time variability for online signature verification. The two reference systems presented in this chapter are also used and evaluated in the BMEC’2007 evaluation campaign, presented in Chap11. ©Springer 2009

    Ladda ner fulltext (pdf)
    fulltext
  • 116.
    Ge, Yu
    et al.
    Chalmers University of Technology, Gothenburg, Sweden.
    Kaltiokallio, Ossi
    Tampere University, Tampere, Finland.
    Chen, Hui
    Chalmers University of Technology, Gothenburg, Sweden.
    Jiang, Fan
    Chalmers University of Technology, Gothenburg, Sweden.
    Talvitie, Jukka
    Tampere University, Tampere, Finland.
    Valkama, Mikko
    Tampere University, Tampere, Finland.
    Svensson, Lennart
    Chalmers University of Technology, Gothenburg, Sweden.
    Wymeersch, Henk
    Chalmers University of Technology, Gothenburg, Sweden.
    Doppler Exploitation in Bistatic mmWave Radio SLAM2022Ingår i: 2022 IEEE Global Communications Conference (GLOBECOM): Proceedings: Rio de Janeiro, Brazil 4-8 December 2022, Piscataway: IEEE, 2022, s. 6463-6468Konferensbidrag (Refereegranskat)
    Abstract [en]

    Networks in 5G and beyond utilize millimeter wave (mmWave) radio signals, large bandwidths, and large antenna arrays, which bring opportunities in jointly localizing the user equipment and mapping the propagation environment, termed as simultaneous localization and mapping (SLAM). Existing approaches mainly rely on delays and angles, and ignore the Doppler, although it contains geometric information. In this paper, we study the benefits of exploiting Doppler in SLAM through deriving the posterior Cramér-Rao bounds (PCRBs) and formulating the extended Kalman-Poisson multi-Bernoulli sequential filtering solution with Doppler as one of the involved measurements. Both theoretical PCRB analysis and simulation results demonstrate the efficacy of utilizing Doppler. © 2022 IEEE

  • 117.
    Gelzinis, Adas
    et al.
    Kaunas University of Technology, Kaunas, Lithuania.
    Verikas, Antanas
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab). Kaunas University of Technology, Kaunas, Lithuania.
    Bacauskiene, Marija
    Kaunas University of Technology, Kaunas, Lithuania.
    Vaiciukynas, Evaldas
    Kaunas University of Technology, Kaunas, Lithuania.
    Learning Accurate Active Contours2013Ingår i: Engineering Applications of Neural Networks: 14th International Conference, EANN 2013, Halkidiki, Greece, September 13-16, 2013 Proceedings, Part I / [ed] Lazaros Iliadis, Harris Papadopoulos & Chrisina Jayne, Berlin Heidelberg: Springer Berlin/Heidelberg, 2013, Vol. 383, s. 396-405Konferensbidrag (Refereegranskat)
    Abstract [en]

    Focus of research in Active contour models (ACM) area is mainly on development of various energy functions based on physical intuition. In this work, instead of designing a new energy function, we generate a multitude of contour candidates using various values of ACM parameters, assess their quality, and select the most suitable one for an object at hand. A random forest is trained to make contour quality assessments. We demonstrate experimentally superiority of the developed technique over three known algorithms in the P. minimum cells detection task solved via segmentation of phytoplankton images. © Springer-Verlag Berlin Heidelberg 2013.

    Ladda ner fulltext (pdf)
    fulltext
  • 118.
    Gelzinis, Adas
    et al.
    Kaunas University of Technology, Kaunas, Lithuania.
    Verikas, Antanas
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab). Kaunas University of Technology, Kaunas, Lithuania.
    Vaiciukynas, Evaldas
    Kaunas University of Technology, Kaunas, Lithuania.
    Bacauskiene, Marija
    Kaunas University of Technology, Kaunas, Lithuania.
    Šulčius, Sigitas
    Marine Science and Technology Center, Klaipeda University, Klaipeda, Lithuania & Open Access Centre for Nature Research, Nature Research Centre, Vilnius, Lithuania.
    Staniulis, Juozas
    Laboratory of Plant Viruses, Nature Research Centre, Institute of Botany, Vilnius, Lithuania.
    Paškauskas, Ričardas
    Marine Science and Technology Center, Klaipeda University, Klaipeda, Lithuania & Laboratory of Algology and Microbial Ecology, Nature Research Centre, Vilnius, Lithuania.
    Automatic detection and morphological delineation of bacteriophages in electron microscopy images2015Ingår i: Computers in Biology and Medicine, ISSN 0010-4825, E-ISSN 1879-0534, Vol. 64, s. 101-116Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Automatic detection, recognition and geometric characterization of bacteriophages in electron microscopy images was the main objective of this work. A novel technique, combining phase congruency-based image enhancement, Hough transform-, Radon transform- and open active contours with free boundary conditions-based object detection was developed to detect and recognize the bacteriophages associated with infection and lysis of cyanobacteria Aphanizomenon flos-aquae. A random forest classifier designed to recognize phage capsids provided higher than 99% accuracy, while measurable phage tails were detected and associated with a correct capsid with 81.35% accuracy. Automatically derived morphometric measurements of phage capsids and tails exhibited lower variability than the ones obtained manually. The technique allows performing precise and accurate quantitative (e.g. abundance estimation) and qualitative (e.g. diversity and capsid size) measurements for studying the interactions between host population and different phages that infect the same host. © 2015 Elsevier Ltd.

  • 119.
    GHIMIRE, SWATANTRA
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Laboratoriet för intelligenta system.
    Speech Intelligibility Measurement on the basis of ITU-T Recommendation P.8632012Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Objective speech intelligibility measurement techniques like AI (Articulation Index) and AI based STI (Speech Transmission Index) fail to assess speech intelligibility in modern telecommunication networks that use several non-linear processing for enhancing speech. Moreover, these techniques do not allow prediction of single individual CVC (Consonant Vowel Consonant) word intelligibility scores. ITU-T P.863 standard [1], which was developed for assessing speech quality, is used as a starting point to develop a simple new model for predicting subjective speech intelligibility of individual CVC words. Subjective intelligibility measurements were carried out for a large set of speech degradations. The subjective test uses single CVC word presentations in an eight alternative closed response set experiment. Subjects assess individual degraded CVC words and an average of correct recognition is used as the intelligibility score for a particular CVC word. The first subjective database uses CVC words that have variations in the first consonant i.e. /C/ous (represented as "kæʊs" using International Phonetic Association phonetic alphabets). This database is used for developing the objective model, while a new database based on VC words (Vowel Consonant) that uses variations in the second consonant (a/C/ e.g. aH, aL) is used for validating the model.

    ITU-T P.863 shows very poor results with a correlation of 0.30 for the first subjective database. A first extension to make P.863 suited for intelligibility prediction is done by restructuring speech material to meet the temporal structure requirements (speech+silence+speech) set for standard P.863 measurements. The restructuring is done by concatenating every original and degraded CVC word with itself. There is no significant improvement in correlation (0.34) when using P.863 on the restructured first subjective database (speech material meets temporal requirements).  In this thesis a simple model based on P.863 is developed for assessing intelligibility of individual CVC words. The model uses a linear combination of a simple time clipping indicator (missing speech parts) and a “Good frame count” indicator which is based on the local perceptual (frame by frame) signal to noise ratio. Using this model on the restructured first database, a reasonably good correlation of 0.81 is seen between subjective scores and the model output values. For the validation database, a correlation of around 0.76 is obtained. Further validation on an existing database at TNO, which uses time clipping degradation only, shows an excellent correlation of 0.98.

    Although a reasonably good correlation is seen on the first database and the validation database, it is too low for reliable measurements. Further validation and development is required, nevertheless the results show that a perception-based technique that uses internal representations of signals can be used for predicting subjective intelligibility scores of individual CVC words.

    Ladda ner fulltext (pdf)
    Speech Intelligibility Measurement on the basis of ITU-T Recommendation P.863
  • 120.
    Gholami Shahbandi, Saeed
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Semantic Mapping in Warehouses2016Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    This thesis and appended papers present the process of tacking the problem of environment modeling for autonomous agent. More specifically, the focus of the work has been semantic mapping of warehouses. A semantic map for such purpose is expected to be layout-like and support semantics of both open spaces and infrastructure of the environment. The representation of the semantic map is required to be understandable by all involved agents (humans, AGVs and WMS.) And the process of semantic mapping is desired to lean toward full-autonomy, with minimum input requirement from human user. To that end, we studied the problem of semantic annotation over two kinds of spatial map from different modalities. We identified properties, structure, and challenges of the problem. And we have developed representations and accompanied methods, while meeting the set criteria. The overall objective of the work is “to develop and construct a layer of abstraction (models and/or decomposition) for structuring and facilitate access to salient information in the sensory data. This layer of abstraction connects high level concepts to low-level sensory pattern.” Relying on modeling and decomposition of sensory data, we present our work on abstract representation for two modalities (laser scanner and camera) in three appended papers. Feasibility and the performance of the proposed methods are evaluated over data from real warehouse. The thesis conclude with summarizing the presented technical details, and drawing the outline for future work.

    Ladda ner fulltext (pdf)
    saesha_lic.pdf
    Ladda ner (pdf)
    saesha_lic_errata.pdf
  • 121.
    Gholami Shahbandi, Saeed
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Åstrand, Björn
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Modeling of a Large Structured Environment: With a Repetitive Canonical Geometric-Semantic Model2014Ingår i: Advances in Autonomous Robotics Systems: 15th Annual Conference, TAROS 2014, Birmingham, UK, September 1-3, 2014. Proceedings / [ed] Michael Mistry, Aleš Leonardis, Mark Witkowski & Chris Melhuish, Heidelberg: Springer, 2014, Vol. 8717, s. 1-12Konferensbidrag (Refereegranskat)
    Abstract [en]

    AIMS project attempts to link the logistic requirements of an intelligent warehouse and state of the art core technologies of automation, by providing an awareness of the environment to the autonomous systems and vice versa. In this work we investigate a solution for modeling the infrastructure of a structured environment such as warehouses, by the means of a vision sensor. The model is based on the expected pattern of the infrastructure, generated from and matched to the map. Generation of the model is based on a set of tools such as closed-form Hough transform, DBSCAN clustering algorithm, Fourier transform and optimization techniques. The performance evaluation of the proposed method is accompanied with a real world experiment. © 2014 Springer International Publishing.

    Ladda ner fulltext (pdf)
    fulltext
  • 122.
    Gholami Shahbandi, Saeed
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Åstrand, Björn
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Philippsen, Roland
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Sensor Based Adaptive Metric-Topological Cell Decomposition Method for Semantic Annotation of Structured Environments2014Ingår i: 2014 13th International Conference on Control Automation Robotics & Vision (ICARCV), Piscataway, NJ: IEEE Press, 2014, s. 1771-1777, artikel-id 7064584Konferensbidrag (Refereegranskat)
    Abstract [en]

    A fundamental ingredient for semantic labeling is a reliable method for determining and representing the relevant spatial features of an environment. We address this challenge for planar metric-topological maps based on occupancy grids. Our method detects arbitrary dominant orientations in the presence of significant clutter, fits corresponding line features with tunable resolution, and extracts topological information by polygonal cell decomposition. Real-world case studies taken from the target application domain (autonomous forklift trucks in warehouses) demonstrate the performance and robustness of our method, while results from a preliminary algorithm to extract corridors, and junctions, demonstrate its expressiveness. Contribution of this work starts with the formulation of metric-topological surveying of environment, and a generic n-direction planar representation accompanied with a general method for extracting it from occupancy map. The implementation also includes some semantic labels specific to warehouse like environments. © 2014 IEEE.

    Ladda ner fulltext (pdf)
    fulltext
  • 123.
    Gilperez, A.
    et al.
    Universidad Autonoma de Madrid, Spain.
    Alonso-Fernandez, Fernando
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Pecharroman, S.
    Universidad Autonoma de Madrid, Spain.
    Fierrez, J.
    Universidad Autonoma de Madrid, Spain.
    Ortega-Garcia, J.
    Universidad Autonoma de Madrid, Spain.
    Off-line Signature Verification Using Contour Features2008Ingår i: Proceedings: eleventh International Conference on Frontiers in Handwriting Recognition, Montréal, Québec - Canada, August 19-21, 2008, Montréal: CENPARMI, Concordia University , 2008Konferensbidrag (Refereegranskat)
    Abstract [en]

    An off-line signature verification system based on contour features is presented. It works at the local image level, and encodes directional properties of signature contours and the length of regions enclosed inside letters. Results obtained on a sub-corpus of the MCYT signature database shows that directional-based features work much better than length-based features. Results are comparable to existing approaches based on different features. It is also observed that combination of the proposed features does not provide improvements in performance, maybe to some existing correlation among them.

    Ladda ner fulltext (pdf)
    fulltext
  • 124.
    Gonzalez, Ramon
    et al.
    Massachusetts Institute of Technology, Cambridge, MA, USA.
    Byttner, Stefan
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Iagnemma, Karl
    Massachusetts Institute of Technology, Cambridge, MA, USA.
    Comparison of Machine Learning Approaches for Soil Embedding Detection of Planetary Exploration Rovers2016Ingår i: Proceedings of the 8th ISTVS Americas Conference, Detroit, September 12-14, 2016., 2016Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper analyzes the advantages and limitations of known machine learning approaches to cope with the problem of incipient rover embedding detection based on propioceptive signals. In particular, two supervised learning approaches (Support Vector Machines and Feed-forward Neural Networks) are compared to two unsupervised learning approaches (K-means and Self-Organizing Maps) in order to identify various degrees of slip (e.g. low slip, moderate slip, high slip). A real dataset collected by a single-wheel testbed available at MIT has been used to validate each strategy. The SVM algorithm achieves the best performance (accuracy >95 %). However, the SOM algorithm represents a better solution in terms of accuracy and the need of hand-labeled data for training the classifier (accuracy >84 %).

  • 125.
    Gonzalez-Sosa, Ester
    et al.
    Nokia Bell-Labs, Madrid, Spain & Universidad Autonoma de Madrid, Madrid, Spain.
    Fierrez, Julian
    Universidad Autonoma de Madrid, Madrid, Spain.
    Vera-Rodriguez, Ruben
    Universidad Autonoma de Madrid, Madrid, Spain.
    Alonso-Fernandez, Fernando
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Facial Soft Biometrics for Recognition in the Wild: Recent Works, Annotation and Evaluation2018Ingår i: IEEE Transactions on Information Forensics and Security, ISSN 1556-6013, E-ISSN 1556-6021, Vol. 13, nr 8, s. 2001-2014Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The role of soft biometrics to enhance person recognition systems in unconstrained scenarios has not been extensively studied. Here, we explore the utility of the following modalities: gender, ethnicity, age, glasses, beard, and moustache. We consider two assumptions: 1) manual estimation of soft biometrics and 2) automatic estimation from two commercial off-the-shelf systems (COTS). All experiments are reported using the labeled faces in the wild (LFW) database. First, we study the discrimination capabilities of soft biometrics standalone. Then, experiments are carried out fusing soft biometrics with two state-of-the-art face recognition systems based on deep learning. We observe that soft biometrics is a valuable complement to the face modality in unconstrained scenarios, with relative improvements up to 40%/15% in the verification performance when using manual/automatic soft biometrics estimation. Results are reproducible as we make public our manual annotations and COTS outputs of soft biometrics over LFW, as well as the face recognition scores. © 2018 IEEE.

  • 126.
    Gonzalez-Sosa, Ester
    et al.
    Universidad Autonoma de Madrid, Madrid, Spain.
    Vera-Rodriguez, Ruben
    Universidad Autonoma de Madrid, Madrid, Spain.
    Fierrez, Julian
    Universidad Autonoma de Madrid, Madrid, Spain.
    Alonso-Fernandez, Fernando
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Patel, Vishal M.
    Rutgers University, NJ, USA.
    Exploring Body Texture From mmW Images for Person Recognition2019Ingår i: IEEE Transactions on Biometrics, Behavior, and Identity Science, E-ISSN 2637-6407, Vol. 1, nr 2, s. 139-151Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Imaging using millimeter waves (mmWs) has many advantages including the ability to penetrate obscurants, such as clothes and polymers. After having explored shape information retrieved from mmW images for person recognition, in this paper we aim to gain some insight about the potential of using mmW texture information for the same task, considering not only the mmW face, but also mmW torso and mmW wholebody. We report experimental results using the mmW TNO database consisting of 50 individuals based on both hand-crafted and learned features from Alexnet and VGG-face pretrained convolutional neural networks (CNNs) models. First, we analyze the individual performance of three mmW body parts, concluding that: 1) mmW torso region is more discriminative than mmW face and the whole body; 2) CNN features produce better results compared to hand-crafted features on mmW faces and the entire body; and 3) hand-crafted features slightly outperform CNN features on mmW torso. In the second part of this paper, we analyze different multi-algorithmic and multi-modal techniques, including a novel CNN-based fusion technique, improving verification results to 2% EER and identification rank-1 results up to 99%. Comparative analyses with mmW body shape information and face recognition in the visible and NIR spectral bands are also reported.

  • 127.
    Grimsholm, Filip
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi.
    Saarmann, Martin
    Högskolan i Halmstad, Akademin för informationsteknologi.
    ESPRIT for DOA estimation2023Självständigt arbete på grundnivå (kandidatexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
    Abstract [sv]

    Radar är ett verktyg som har haft en enorm påverkan sen dess upptäckt. Denna avhandling utvärderar en algoritm som heter ESPRIT. ESPRIT används i radar för att estimera vinklarna till detekterade objekt. Vinkeln för ett objekt benämns som dess DOA (Direction of arrival). ESPRIT skiljer sig från liknande algoritmer genom dess lägre beräkningskomplexitet, lagringsbehov samt robusthet.

    Avhandlingen jämför ESPRIT med en annan DOA estimerings algoritm som används av företaget Raytelligence idag. På grund av sekretess kan denna algoritm inte namnges. Jämförelsen bygger på praktiskt insamlad data från en FMCW (Frequency Modulated Continious Wave) radar. Jämförelsen siktar på att validera att ESPRIT fungerar, samt dess konkurrersförmåga mot den andra algoritmen. Jämförelsen utgick från två kriterier: Noggranhet och komplexitet. Avhandlingen presenterar även möjliga optimiseringar som kan förbättra ESPRITs förmåga att estimera DOA. Dessa är ökning av antalet antenner som används i DOA estimeringen, samt att använda förbehandlingsschemat Spatial smoothing.

    Resultatet för DOA estimering visar att ESPRITs' styrka ligger i att kunna detektera flera objekt på samma avstånd. Skillnaden mellan ESPRIT och den andra DOA estimerings algoritmen, vid estimering av ett objekt var inte tillräckligt signifikant för att dra några slutsatser. Resultatet visade också att ESPRITs' prestationsförmåga ökar med antalet antenner, samt vilket förbehandlingsschema som används.

    Resultatet för komplexitet visade att ESPRIT har högre komplexitet än den andra DOA estimerings algoritmen. För att ESPRIT ska kunna nyttja sin styrka, att kunna detektera flera objekt på samma distans, krävs implementation av komplexa förbehandlingsscheman. Detta ökar skillnaden på komplexitet mellan de två jämförda algoritmerna ytterliggare.

    Ladda ner fulltext (pdf)
    fulltext
  • 128.
    Grip, Andreas
    Högskolan i Halmstad, Akademin för informationsteknologi.
    Kraftmätning på cykelpedal2018Självständigt arbete på grundnivå (högskoleexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
    Abstract [en]

    This report will describe the development of a subsystem for force measurement on bicycle pedals. The force is going to be used as a control parameter in a motor controller to control an electric motor on an electric bicycle. The report focuses on force measurement and will not process any control system. There has also been a survey of alternative power supplies to the circuit boards to be used in this project. Energy Harvesting has been investigated as an alternative source. The aim of the project is to measure the force applied on the pedal in a good way for use in a control system.This work resulted in that the force applied on the pedals was measured on the crank arms. The force was being measured by strain gauge sensors in a test rig designed in this project. The force signal can be used in the intended control system. This report has explained when, during a pedal stroke, the force should be measured. Processing of the signal will be done furthermore in the motor controller to fit the requirements set by the control system.

    Ladda ner fulltext (pdf)
    fulltext
  • 129.
    Guzmán Bacarreza, Victor
    et al.
    Högskolan i Halmstad, Akademin för företagande, innovation och hållbarhet.
    Andersson, Claes
    Högskolan i Halmstad, Akademin för företagande, innovation och hållbarhet.
    INTI: En automatiserad ljudupplevelse2021Självständigt arbete på grundnivå (yrkesexamen), 15 poäng / 22,5 hpStudentuppsats (Examensarbete)
    Abstract [sv]

    Examensarbetet INTI grundades i samband med projektmedlemmarnas stora intresse för den utveckling som har skett av elektroniska produkter till det som klassificeras som smarta hemprodukter idag. Genom att applicera tre års lärdomar inom produkt- och projektledning idetta examensarbete utformades en automatiserad lösning vilket baseras på platsidentifiering. Iskrivande stund finns det ett flertal olika varianter av smarta produkter inom diversemarknadssegment, exempelvis högtalare, lampor samt säkerhetsprodukter. Det som projektdeltagarna vill eftersträva med projektet är att skapa ett automatiserat system (INTI) somintegreras med ett par ljudenheter och skapar ett follow-around system för användaren.INTI är en automatiserad systematisk lösning, där det har tillämpats programmering av modulerför att på ett effektivt sätt skapa ett positioneringssystem för att lokalisera användaren. Genomatt platsidentifiera användarens position ges möjligheten till att anpassa tekniskakonfigureringar i ljudenheterna och etablera ett follow-around system. Det primäraproduktmålet för detta examensarbete är att sammanlänka INTI med två högtalare och uppnåett funktionellt follow-around system, vilket innefattar att ljudenheterna anpassar volymen utefter användarens position. Syftet med detta examensarbete är att skapa en unik lösning somär prisvärt och underlättar vardagen för privatkonsumenter.

    Ladda ner fulltext (pdf)
    fulltext
  • 130.
    Hagström, Adrian Leo
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi.
    Stanikzai, Rustam
    Högskolan i Halmstad, Akademin för informationsteknologi.
    Bigun, Josef
    Högskolan i Halmstad, Akademin för informationsteknologi.
    Alonso-Fernandez, Fernando
    Högskolan i Halmstad, Akademin för informationsteknologi.
    Writer Recognition Using Off-line Handwritten Single Block Characters2022Konferensbidrag (Refereegranskat)
    Abstract [en]

    Block characters are often used when filling paper forms for a variety of purposes. We investigate if there is biometric information contained within individual digits of handwritten text. In particular, we use personal identity numbers consisting of the six digits of the date of birth, DoB. We evaluate two recognition approaches, one based on handcrafted features that compute contour directional measurements, and another based on deep features from a ResNet50 model. We use a self-captured database of 317 individuals and 4920 written DoBs in total. Results show the presence of identity-related information in a piece of handwritten information as small as six digits with the DoB. We also analyze the impact of the amount of enrolment samples, varying its number between one and ten. Results with such small amount of data are promising. With ten enrolment samples, the Top-1 accuracy with deep features is around 94%, and reaches nearly 100% by Top-10. The verification accuracy is more modest, with EER>20% with any given feature and enrolment set size, showing that there is still room for improvement.

    Ladda ner fulltext (pdf)
    fulltext
  • 131.
    Hansson, Jörgen
    et al.
    Volvo Group Trucks Technology, Göteborg, Sweden.
    Svensson, Magnus
    Volvo Group Trucks Technology, Göteborg, Sweden.
    Rögnvaldsson, Thorsteinn
    Volvo Group Trucks Technology, Göteborg, Sweden.
    Byttner, Stefan
    Volvo Group Trucks Technology, Göteborg, Sweden.
    Remote Diagnosis Modelling2008Patent (Övrig (populärvetenskap, debatt, mm))
    Abstract [en]

    A diagnosis and maintenance method, a diagnosis and maintenance assembly comprising a central server and a system, and a computer program for diagnosis and maintenance for a plurality of systems, particularly for a plurality of vehicles, wherein each system provides at least one system-related signal which provides the basis for the diagnosis and/or maintenance of/for the system are provided. The basis for diagnosis and/or maintenance is determined by determining for each system at least one relation between the system-related signals, comparing the compatible determined relations, determining for the plurality of systems based on the result of the comparison which relations are significant relations and providing a diagnosis and/or maintenance decision based on the determined significant relations.

    Ladda ner fulltext (pdf)
    fulltext
  • 132.
    Hashemzadeh, Parham
    Högskolan i Halmstad, Sektionen för ekonomi och teknik (SET), Maskinteknisk produktframtagning (MTEK), Fotonik.
    Parametric Reconstruction of Objects Using Microwave Measurements2009Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
  • 133.
    Hedenberg, Klas
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab). University of Skövde, Skövde, Sweden.
    Obstacle Detection for Driverless Trucks in Industrial Environments2014Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    With an increased demand on productivity and safety in industry, new issues in terms of automated material handling arise. This results in industries not having a homogenous fleet of trucks and driven and driverless trucks are mixed in a dynamic environment. Driven trucks are more flexible than driverless trucks, but are also involved in more accidents. A transition from driven to driverless trucks can increase safety, but also productivity in terms of fewer accidents and more accurate delivery. Hence, reliable and standardized solutions that avoid accidents are important to achieve high productivity and safety. There are two different safety standards for driverless trucks for Europe (EN1525) and U.S. (B56.5–2012) and they have developed differently. In terms of obstacles, they both consider contact with humans. However, a machinery-shaped object has recently been added to the U.S. standard (B56.5–2012). The U.S. standard also considers different materials for different sensors and non-contact sensors. For obstacle detection, the historical contact-sensitive mechanical bumpers as well as the traditional laser scanner used today both have limitations – they do not detect hanging objects. In this work we have identified several thin objects that are of interest in an industrial environment. A test apparatus with a thin structure is introduced for a more uniform way to evaluate sensors. To detect thin obstacles, we used a standard setup of a stereo system and developed this further to a trinocular system (a stereo system with three cameras). We also propose a method to evaluate 3D sensors based on the information from a 2D range sensor. The 3D model is created by measuring the position of a reflector with known position to an object with a known size. The trinocular system, a 3D TOF camera and a Kinect sensor are evaluated with this method. The results showed that the method can be used to evaluate sensors. It also showed that 3D sensor systems have potential to be used on driverless trucks to detect obstacles, initially as a complement to existing safety classed sensors. To improve safety and productivity, there is a need for harmonization of the European and the U.S. safety standards. Furthermore, parallel development of sensor systems and standards is needed to make use of state-of-the-art technology for sensors.

    Ladda ner fulltext (pdf)
    fulltext
  • 134.
    Hedenberg, Klas
    et al.
    University of Skövde, School of Technology and Society, Skövde, Sweden.
    Baerveldt, Albert-Jan
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Stereo vision-based collision avoidance2004Ingår i: The 9th Mechatronics Forum International Conference: Conference Proceedings, Ankara: Atılım University , 2004, s. 259-270Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper investigates whether a stereo vision system based on points of interest is robust enough to detect obstacles for applications like a mobile robot in an industrial environment and for the visually impaired. Points of interest are extracted with a known method, called KLT. Two algorithms to solve the correspondence problem (Sum of Squared Difference and Variance Normalized Correlation) are used and evaluated as well as a combination of the two. An improvement is made if the two algorithms are combined. The tests show that stereo vision based on points of interest only can be used robustly for obstacle detection if there is enough texture on the obstacle. Otherwise too few points of interest on the object are detected and a reliable estimation of the distance to the object cannot be made.

  • 135.
    Hedenberg, Klas
    et al.
    Skövde University, Skövde, Sweden.
    Åstrand, Björn
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    3D Sensors on Driverless Trucks for Detection of Overhanging Objects in the Pathway2015Ingår i: Autonomous Industrial Vehicles: From the Laboratory to the Factory Floor / [ed] Roger Bostelman & Elena Messina, Conshohocken: ASTM International, 2015, s. 41-56Kapitel i bok, del av antologi (Refereegranskat)
    Abstract [en]

    Human-operated and driverless trucks often collaborate in a mixed work space in industries and warehouses. This is more efficient and flexible than using only one kind of truck. However, since driverless trucks need to give way to trucks, a reliable detection system is required. Several challenges exist in the development of an obstacle detection system in an industrial setting. The first is to select interesting situations and objects. Overhanging objects are often found in industrial environments, e.g. tines on a forklift. Second is choosing a detection system that has the ability to detect those situations. The traditional laser scanner situated two decimetres above the floor does not detect overhanging objects. Third is to ensure that the perception system is reliable. A solution used on trucks today is to mount a 2D laser scanner on the top of the truck and tilt the scanner towards the floor. However, objects at the top of the truck will be detected too late and a collision cannot always be avoided. Our aim is to replace the upper 2D laser scanner with a 3D camera, structural light or time-of-flight (TOF) camera. It is important to maximize the field of view in the desired detection volume. Hence, the placement of the sensor is important. We conducted laboratory experiments to check and compare the various sensors’ capabilities for different colors, used tines and a model of a tine in a controlled industrial environment. We also conducted field experiments in a warehouse. The conclusion is that both the tested structural light and TOF sensors have problems to detect black items that is nonperpendicular to the sensor and at the distance of interest. It is important to optimize the light economy, meaning the illumination power, field of view and exposure time in order to detect as many different objects as possible. Copyright © 2016 by ASTM International

    Ladda ner fulltext (pdf)
    fulltext
  • 136.
    Hedman, Pontus
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi.
    Skepetzis, Vasilios
    Högskolan i Halmstad, Akademin för informationsteknologi.
    Hernandez-Diaz, Kevin
    Högskolan i Halmstad, Akademin för informationsteknologi.
    Bigun, Josef
    Högskolan i Halmstad, Akademin för informationsteknologi.
    Alonso-Fernandez, Fernando
    Högskolan i Halmstad, Akademin för informationsteknologi.
    On the effect of selfie beautification filters on face detection and recognition2022Ingår i: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 163, s. 104-111Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Beautification and augmented reality filters are very popular in applications that use selfie images. However, they can distort or modify biometric features, severely affecting the ability to recognise the individuals’ identity or even detect the face. Accordingly, we address the effect of such filters on the accuracy of automated face detection and recognition. The social media image filters studied modify the image contrast, illumination, or occlude parts of the face. We observe that the effect of some of these filters is harmful to face detection and identity recognition, especially if they obfuscate the eye or (to a lesser extent) the nose. To counteract such effect, we develop a method to reverse the applied manipulation with a modified version of the U-NET segmentation network. This method is observed to contribute to better face detection and recognition accuracy. From a recognition perspective, we employ distance measures and trained machine learning algorithms applied to features extracted using several CNN backbones. We also evaluate if incorporating filtered images into the training set of machine learning approaches is beneficial. Our results show good recognition when filters do not occlude important landmarks, especially the eyes. The combined effect of the proposed approaches also allows mitigating the impact produced by filters that occlude parts of the face. © 2022 The Authors. Published by Elsevier B.V.

    Ladda ner fulltext (pdf)
    fulltext
  • 137.
    Helldin, Tove
    et al.
    University of Skövde, Skövde, Sweden.
    Riveiro, Maria
    University of Skövde, Skövde, Sweden.
    Pashami, Sepideh
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Falkman, Göran
    University of Skövde, Skövde, Sweden.
    Byttner, Stefan
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Slawomir, Nowaczyk
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Supporting Analytical Reasoning: A Study from the Automotive Industry2016Ingår i: Human Interface and the Management of Information: Applications and Services: 18th International Conference, HCI International 2016: Toronto, Canada, July 17-22, 2016. Proceedings, Part II / [ed] Sakae Yamamoto, Cham: Springer, 2016, Vol. 9735, s. 20-31Konferensbidrag (Refereegranskat)
    Abstract [en]

    In the era of big data, it is imperative to assist the human analyst in the endeavor to find solutions to ill-defined problems, i.e. to “detect the expected and discover the unexpected” (Yi et al., 2008). To their aid, a plethora of analysis support systems is available to the analysts. However, these support systems often lack visual and interactive features, leaving the analysts with no opportunity to guide, influence and even understand the automatic reasoning performed and the data used. Yet, to be able to appropriately support the analysts in their sense-making process, we must look at this process more closely. In this paper, we present the results from interviews performed together with data analysts from the automotive industry where we have investigated how they handle the data, analyze it and make decisions based on the data, outlining directions for the development of analytical support systems within the area. © Springer International Publishing Switzerland 2016.

  • 138. Hellsten, Hans
    et al.
    Nilsson, Emil
    Multiple Access Radar Using Slow Chirp Modulation2020Ingår i: 2020 IEEE Radar Conference (RadarConf20), New York, NY: IEEE, 2020, s. 1-6Konferensbidrag (Refereegranskat)
    Abstract [en]

    The cohabitation of several radars, operating in the same frequency band, has become an essential and urgent topic as active safety systems for automotive applications are rolled out. An obvious concern is that mutual interference must be managed. Separating users in time, i.e. TDMA, achieves the required level of isolation in a straightforward way. CDMA techniques providing sufficient channel isolation are less obvious. The paper develops an alternative CDMA method, called Slow Chirp Modulation (SCM). SCM utilizes the full coherent integration time for transmission of a single aperiodic but ergodic signal, allowing target range and velocity to be retrieved but minimizing spectral occupancy. Spectral efficiency two orders of magnitude higher than for the discussed alternative methods is obtained, allowing more than a thousand non-interfering channels. Relying on indicated hardware schematics, the paper demonstrates the functionality of the novel signal processing algorithms, which are required for SCM. ©2020 IEEE

  • 139.
    Henriksson, Jens
    et al.
    Semcon AB, Gothenburg, Sweden.
    Berger, Christian
    University of Gothenburg, Gothenburg, Sweden & Chalmers Institute of Technology, Gothenburg, Sweden.
    Borg, Markus
    RISE Research Institutes of Sweden AB, Lund and Gothenburg, Sweden.
    Tornberg, Lars
    Machine Learning and AI Center of Excellence, Volvo Cars, Gothenburg, Sweden.
    Sathyamoorthy, Sankar
    QRTech AB, Gothenburg, Sweden.
    Englund, Cristofer
    RISE Research Institutes of Sweden AB, Lund and Gothenburg, Sweden.
    Performance Analysis of Out-of-Distribution Detection on Various Trained Neural Networks2019Ingår i: Proceedings. 45th Euromicro Conference on Software Engineering and Advanced Applications. SEAA 2019: 28 - 30 August 2019 Kallithea, Chalkidiki, Greece / [ed] Staron, M., Capilla, R. & Skavhaug, A., Piscataway: IEEE, 2019Konferensbidrag (Refereegranskat)
    Abstract [en]

    Several areas have been improved with Deep Learning during the past years. For non-safety related products adoption of AI and ML is not an issue, whereas in safety critical applications, robustness of such approaches is still an issue. A common challenge for Deep Neural Networks (DNN) occur when exposed to out-of-distribution samples that are previously unseen, where DNNs can yield high confidence predictions despite no prior knowledge of the input. In this paper we analyse two supervisors on two well-known DNNs with varied setups of training and find that the outlier detection performance improves with the quality of the training procedure. We analyse the performance of the supervisor after each epoch during the training cycle, to investigate supervisor performance as the accuracy converges. Understanding the relationship between training results and supervisor performance is valuable to improve robustness of the model and indicates where more work has to be done to create generalized models for safety critical applications. © 2019 IEEE

  • 140.
    Hernandez-Diaz, Kevin
    Högskolan i Halmstad, Akademin för informationsteknologi.
    Ocular Recognition in Unconstrained Sensing Environments2024Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    This thesis focuses on the problem of increasing flexibility in the acquisition and application of biometric recognition systems based on the ocular region. While the ocular area is one of the oldest and most widely studied biometric regions thanks to its rich and discriminative elements and characteristics, most modalities such as retina, iris, eye movements, or oculomotor plant have limitations regarding data acquisition. Some require a specific type of illumination like the iris, a limited distance range like eye movements, or specific sensors and user collaboration like the retina. In this context, this thesis focuses on the periocular region, which stands out as the ocular modality with the fewest acquisition constraints. 

    The first part focuses on using middle-layers' deep representation of pre-trained CNNs as a one-shot learning method, along with simple distance-based metrics and similarity scores for periocular recognition. This approach tackles the issue of limited data availability and collection for biometric recognition systems by eliminating the need to train the models for the target data. Furthermore, it allows seamless transitions between identification and verification scenarios with a single model, and tackles the problem of the open-world setting and training bias of CNNs. We demonstrate that off-the-shelf features from middle-layers can outperform CNNs trained for the target domain that followed a more extensive training strategy when target data is limited.

    The second part of the thesis analyzes traditional methods for biometric systems in the context of periocular recognition. Nowadays, these methods are often overlooked in favor of deep learning solutions. However, we show that they can still outperform heavily trained CNNs in closed-world and open-world settings and can be used in conjunction with CNNs to further improve recognition performance. Moreover, we investigate the use of the complex structure tensor as a handcrafted texture extractor at the input of CNNs. We show that CNNs can benefit from this explicit textural information in terms of performance and convergence, offering the potential for network compression and explainability of the features used. We demonstrate that CNNs may not easily access the orientation information present in the images that are exploited in some more traditional approaches.

    The final part of the thesis addresses the analysis of periocular recognition under different light spectra and the cross-spectral scenario. More specifically, we analyze the performance of the proposed methods under different light spectra. We also investigate the cross-spectral scenario for one-shot learning with middle-layers' deep representations and explore the possibility of bridging the domain gap in the cross-spectral scenario by training generative networks. This allows using simpler models and algorithms trained on a single spectrum.

    Ladda ner fulltext (pdf)
    fulltext
    Ladda ner (jpg)
    presentationsbild
  • 141.
    Hernandez-Diaz, Kevin
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Alonso-Fernandez, Fernando
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Bigun, Josef
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Cross Spectral Periocular Matching using ResNet Features2019Ingår i: 2019 International Conference on Biometrics (ICB), Piscataway, N.J.: IEEE, 2019Konferensbidrag (Refereegranskat)
    Abstract [en]

    Periocular recognition has gained attention in the last years thanks to its high discrimination capabilities in less constraint scenarios than other ocular modalities. In this paper we propose a method for periocular verification under different light spectra using CNN features with the particularity that the network has not been trained for this purpose. We use a ResNet-101 pretrained model for the ImageNet Large Scale Visual Recognition Challenge to extract features from the IIITD Multispectral Periocular Database. At each layer the features are compared using χ 2 distance and cosine similitude to carry on verification between images, achieving an improvement in the EER and accuracy at 1% FAR of up to 63.13% and 24.79% in comparison to previous works that employ the same database. In addition to this, we train a neural network to match the best CNN feature layer vector from each spectrum. With this procedure, we achieve improvements of up to 65% (EER) and 87% (accuracy at 1% FAR) in cross-spectral verification with respect to previous studies.

    Ladda ner fulltext (pdf)
    fulltext
  • 142.
    Hernandez-Diaz, Kevin
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Alonso-Fernandez, Fernando
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Bigun, Josef
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Cross-Spectral Biometric Recognition with Pretrained CNNs as Generic Feature Extractors2019Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    Periocular recognition has gained attention in the last years thanks to its high discrimination capabilities in less constraint scenarios than face or iris. In this paper we propose a method for periocular verification under different light spectra using CNN features with the particularity that the network has not been trained for this purpose. We use a ResNet-101 pretrained model for the ImageNet Large Scale Visual Recognition Challenge to extract features from the IIITD Multispectral Periocular Database. At each layer the features are compared using χ 2 distance and cosine similitude to carry on verification between images, achieving an improvement in the EER and accuracy at 1% FAR of up to 63.13% and 24.79% in comparison to previous works that employ the same database. In addition to this, we train a neural network to match the best CNN feature layer vector from each spectrum. With this procedure, we achieve improvements of up to 65% (EER) and 87% (accuracy at 1% FAR) in cross-spectral verification with respect to previous studies.

    Ladda ner fulltext (pdf)
    fulltext
  • 143.
    Hernandez-Diaz, Kevin
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Alonso-Fernandez, Fernando
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Bigun, Josef
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Cross-Spectral Periocular Recognition with Conditional Adversarial Networks2020Ingår i: IJCB 2020 : IEEE/IAPR International Joint Conference on Biometrics : 28th September-1st October 2020, online, Piscataway: IEEE, 2020Konferensbidrag (Refereegranskat)
    Abstract [en]

    This work addresses the challenge of comparing periocular images captured in different spectra, which is known to produce significant drops in performance in comparison to operating in the same spectrum. We propose the use of ConditionalGenerative Adversarial Networks, trained to convert periocular images between visible and near-infrared spectra, so that biometric verification is carried out in the same spectrum. The proposed setup allows the use of existing feature methods typically optimized to operate in a single spectrum. Recognition experiments are done using a number of off-the-shelf periocular comparators based both on hand-crafted features and CNN descriptors. Using the Hong Kong Polytechnic University Cross-Spectral Iris Images Database (PolyU) as benchmark dataset, our experiments show that cross-spectral performance is substantially improved if both images are converted to the same spectrum, in comparison to matching features extracted from images in different spectra. In addition to this, we fine-tune a CNN based on the ResNet50 architecture, obtaining a cross-spectral periocular performance of EER=l%, and GAR>99% @ FAR=l%, which is comparable to the state-of-the-art with the PolyU database. © 2020 IEEE.

  • 144.
    Hernandez-Diaz, Kevin
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Alonso-Fernandez, Fernando
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Bigun, Josef
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Periocular Recognition Using CNN Features Off-the-Shelf2018Ingår i: 2018 International Conference of the Biometrics Special Interest Group (BIOSIG), Piscataway, N.J.: IEEE, 2018Konferensbidrag (Refereegranskat)
    Abstract [en]

    Periocular refers to the region around the eye, including sclera, eyelids, lashes, brows and skin. With a surprisingly high discrimination ability, it is the ocular modality requiring the least constrained acquisition. Here, we apply existing pre-trained architectures, proposed in the context of the ImageNet Large Scale Visual Recognition Challenge, to the task of periocular recognition. These have proven to be very successful for many other computer vision tasks apart from the detection and classification tasks for which they were designed. Experiments are done with a database of periocular images captured with a digital camera. We demonstrate that these offthe-shelf CNN features can effectively recognize individuals based on periocular images, despite being trained to classify generic objects. Compared against reference periocular features, they show an EER reduction of up to ~40%, with the fusion of CNN and traditional features providing additional improvements.

    Ladda ner fulltext (pdf)
    fulltext
  • 145.
    Hofbauer, Heinz
    et al.
    University of Salzburg, Salzburg, Austria.
    Alonso-Fernandez, Fernando
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Bigun, Josef
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Uhl, Andreas
    University of Salzburg, Salzburg, Austria.
    Experimental Analysis Regarding the Influence of Iris Segmentation on the Recognition Rate2016Ingår i: IET Biometrics, ISSN 2047-4938, E-ISSN 2047-4946, Vol. 5, nr 3, s. 200-211Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In this study the authors will look at the detection and segmentation of the iris and its influence on the overall performance of the iris-biometric tool chain. The authors will examine whether the segmentation accuracy, based on conformance with a ground truth, can serve as a predictor for the overall performance of the iris-biometric tool chain. That is: If the segmentation accuracy is improved will this always improve the overall performance? Furthermore, the authors will systematically evaluate the influence of segmentation parameters, pupillary and limbic boundary and normalisation centre (based on Daugman's rubbersheet model), on the rest of the iris-biometric tool chain. The authors will investigate if accurately finding these parameters is important and how consistency, that is, extracting the same exact region of the iris during segmenting, influences the overall performance. © The Institution of Engineering and Technology 2016

  • 146.
    Hofbauer, Heinz
    et al.
    Department of Computer Sciences, University of Salzburg, Salzburg, Austria.
    Alonso-Fernandez, Fernando
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Wild, Peter
    Department of Computer Sciences, University of Salzburg, Salzburg, Austria.
    Bigun, Josef
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Uhl, Andreas
    Department of Computer Sciences, University of Salzburg, Salzburg, Austria.
    A Ground Truth for Iris Segmentation2014Ingår i: 2014 22nd International Conference on Pattern Recognition (ICPR) / [ed] Lisa O’Conner, Los Alamitos: IEEE Computer Society, 2014, s. 527-532Konferensbidrag (Refereegranskat)
    Abstract [en]

    Classical iris biometric systems assume ideal environmental conditions and cooperative users for image acquisition. When conditions are less ideal or users are uncooperative or unaware of their biometrics being taken the image acquisition quality suffers. This makes it harder for iris localization and segmentation algorithms to properly segment the acquired image into iris and non-iris parts. Segmentation is a critical part in iris recognition systems, since errors in this initial stage are propagated to subsequent processing stages. Therefore, the performance of iris segmentation algorithms is paramount to the performance of the overall system. In order to properly evaluate and develop iris segmentation algorithm, especially under difficult conditions like off angle and significant occlusions or bad lighting, it is beneficial to directly assess the segmentation algorithm. Currently, when evaluating the performance of iris segmentation algorithms this is mostly done by utilizing the recognition rate, and consequently the overall performance of the biometric system. In order to streamline the development and assessment of iris segmentation algorithms with the dependence on the whole biometric system we have generated a iris segmentation ground truth database. We will show a method for evaluating iris segmentation performance base on this ground truth database and give examples of how to identify problematic cases in order to further analyse the segmentation algorithms. ©2014 IEEE.

    Ladda ner fulltext (pdf)
    fulltext
  • 147.
    Holm, Kasper
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi.
    Henrysson, Erik
    Högskolan i Halmstad, Akademin för informationsteknologi.
    Reconnaissance Radar Robot2023Självständigt arbete på grundnivå (yrkesexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
    Abstract [en]

    During the last century, various countries' armed forces have used unmanned aerial vehicles, commonly known as drones. In recent years, strives have been made to develop small commercial drones that have allowed the general public to afford and use them for recreational purposes. The availability of drones has led to immoral applications of the technology. Such applications need to be faced with anti-measures and effective detection methods. Therefore, this thesis aims to develop a mobile reconnaissance robot that can detect commercial drones with radar. It describes integrating radar sensors with single-board computers to detect and localise air-bound objects. The finished product aims to be used for educational and exhibition purposes at the Swedish Armed Forces technical school to increase awareness of the technology.

    Ladda ner fulltext (pdf)
    fulltext
  • 148.
    Ifver, Joakim
    Högskolan i Halmstad, Akademin för informationsteknologi.
    Predictive Maintenance of Servo Guns2022Självständigt arbete på grundnivå (yrkesexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
    Abstract [sv]

    Detta examensarbete undersöker möjligheten att implementera ett system som detekterar defekter m.h.a. böjningsdata från ABB’s svetstänger. Genom att titta på datan, dvs., elektrodernas position vid varje slag/svets, används flertal metoder för att undersöka processens beteende. Datans distribution visade en god passform till en normalfördelning, vilket ledde projektet till en traditionell metod inom Statistical Process Control (SPC) sk. Control Chart. Efter att man undersökt datans frekvensdomän, om det fanns ett mönster att avläsa och tillämpat Unsupervised clustering, genomfördes flera olika experiment. Det första experimentet undersökte hur böjningen i tångarmarna förändrades genom att applicera olika krafter mellan elektroderna. Dessutom genererades data för att försöka skapa konstgjorda sprickor genom att byta ut elektroder av olika längd. I tillägg skapades drivande data (förändringar i böjning med tiden) genom att applicera små förändringar i kraft mellan elektroderna i ett visst intervall. Idén bakom experimenten var att utvärdera prestationen av en Control Chart, där övre och undre kontrollparametrar bestämdes utifrån en regressionsfunktion som var implementerad m.h.a. parametrar från resultatet utav förhållandet mellan kraft och böjning. Experimenten utfördes på en utav ABB’s svettänger s.k. GWT X9. Metoden visade sig fungera för testen som blev utförda, men resultatet föreslår att arbetet kräver mer foskning och arbete för att bli implementerad i ABB’s mjukvara. 

    Ladda ner fulltext (pdf)
    fulltext
  • 149.
    Ivanenko, Yevhen
    et al.
    Institute Of Technology, Karlskrona, Sweden.
    Vu, Viet T.
    Institute Of Technology, Karlskrona, Sweden.
    Barowski, Jan
    Ruhr University Bochum, Bochum, Germany.
    Hellsten, Hans
    Högskolan i Halmstad, Akademin för informationsteknologi.
    Pettersson, Mats I.
    Institute Of Technology, Karlskrona, Sweden.
    Phase Control in Interpolation for Backprojection of THz FMCW SAR Signals2022Ingår i: 2022 23rd International Radar Symposium (IRS), IEEE, 2022, s. 10-15Konferensbidrag (Refereegranskat)
    Abstract [en]

    The THz frequency spectrum opens a lot of applications in the imaging at sub-mm level. The increase of the operating frequency band for SAR imaging systems to the THz range has proportionally affected the amount of raw data to be stored and used for accurate image reconstruction. As a consequence, improvements in the existing SAR imaging algorithms to reduce the amount of data needed to achieve the appropriate quality of imaging is desired. This paper introduces the phase control procedure as an extension to the existing sinc interpolator for backprojecting complex-valued FMCW SAR data into a defined image plane. The proposed extension controls the phase of interpolated complex-valued SAR data parameters so that it includes appropriate information about the range distance between the SAR system and the given point of space. The extended algorithm is incorporated into the global backprojection algorithm and examined on the measurement data acquired via the 2pSENSE FMCW SAR system. The efficiency of the extended algorithm is evaluated through the comparison with the conventional nearest neighbor and sinc interpolation algorithms. © 2022 Warsaw University of Technology.

  • 150.
    Jaiswal, Amit Kumar
    et al.
    University Of Surrey, Guildford, United Kingdom.
    Liu, Haiming
    University Of Southampton, Southampton, United Kingdom.
    Tiwari, Prayag
    Högskolan i Halmstad, Akademin för informationsteknologi.
    Towards Subject Agnostic Affective Emotion Recognition2023Ingår i: CEUR Workshop Proceedings: Proceedings of the 2nd International Workshop on Multimodal Human Understanding for the Web and Social Media / [ed] Gullal S. Cheema; Sherzod Hakimov; Marc A. Kastner; Noa Garcia, Aachen: Rheinisch-Westfaelische Technische Hochschule Aachen , 2023, Vol. 3566, s. 47-61Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper focuses on affective emotion recognition, aiming to perform in the subject-agnostic paradigm based on EEG signals. However, EEG signals manifest subject instability in subject-agnostic affective Brain-computer interfaces (aBCIs), which led to the problem of distributional shift. Furthermore, this problem is alleviated by approaches such as domain generalisation and domain adaptation. Typically, methods based on domain adaptation confer comparatively better results than the domain generalisation methods but demand more computational resources given new subjects. We propose a novel framework, meta-learning based augmented domain adaptation for subject-agnostic aBCIs. Our domain adaptation approach is augmented through meta-learning, which consists of a recurrent neural network, a classifier, and a distributional shift controller based on a sum-decomposable function. Also, we present that a neural network explicating a sum-decomposable function can effectively estimate the divergence between varied domains. The network setting for augmented domain adaptation follows meta-learning and adversarial learning, where the controller promptly adapts to new domains employing the target data via a few self-adaptation steps in the test phase. Our proposed approach is shown to be effective in experiments on a public aBICs dataset and achieves similar performance to state-of-the-art domain adaptation methods while avoiding the use of additional computational resources. © 2023 Copyright for this paper by its authors.

123456 101 - 150 av 269
RefereraExporteraLänk till träfflistan
Permanent länk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf