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  • 1.
    Alonso-Fernandez, Fernando
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Farrugia, Reuben A.
    University of Malta, Msida, Malta.
    Bigun, Josef
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Fierrez, Julian
    Universidad Autonoma de Madrid, Madrid, Spain.
    Gonzalez-Sosa, Ester
    Nokia Bell-Labs, Madrid, Spain.
    A Survey of Super-Resolution in Iris Biometrics with Evaluation of Dictionary-Learning2019Ingår i: IEEE Access, E-ISSN 2169-3536, Vol. 7, s. 6519-6544Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The lack of resolution has a negative impact on the performance of image-based biometrics. While many generic super-resolution methods have been proposed to restore low-resolution images, they usually aim to enhance their visual appearance. However, an overall visual enhancement of biometric images does not necessarily correlate with a better recognition performance. Reconstruction approaches need thus to incorporate specific information from the target biometric modality to effectively improve recognition performance. This paper presents a comprehensive survey of iris super-resolution approaches proposed in the literature. We have also adapted an Eigen-patches reconstruction method based on PCA Eigentransformation of local image patches. The structure of the iris is exploited by building a patch-position dependent dictionary. In addition, image patches are restored separately, having their own reconstruction weights. This allows the solution to be locally optimized, helping to preserve local information. To evaluate the algorithm, we degraded high-resolution images from the CASIA Interval V3 database. Different restorations were considered, with 15 × 15 pixels being the smallest resolution evaluated. To the best of our knowledge, this is among the smallest resolutions employed in the literature. The experimental framework is complemented with six publicly available iris comparators, which were used to carry out biometric verification and identification experiments. Experimental results show that the proposed method significantly outperforms both bilinear and bicubic interpolation at very low-resolution. The performance of a number of comparators attain an impressive Equal Error Rate as low as 5%, and a Top-1 accuracy of 77-84% when considering iris images of only 15 × 15 pixels. These results clearly demonstrate the benefit of using trained super-resolution techniques to improve the quality of iris images prior to matching. © 2018, Emerald Publishing Limited.

  • 2.
    Lien, Shao-Yu
    et al.
    National Chung Cheng University, Chia-Yi, Taiwan.
    Kuo, Yen-Chih
    National Formosa University, Yulin, Taiwan.
    Deng, Der-Jiunn
    National Changhua University of Education, Changhua, Taiwan.
    Tsai, Hua-Lung
    Industrial Technology Research Institute, Hsinchu, Taiwan.
    Vinel, Alexey
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Benslimane, Abderrahim
    University of Avignon, Avignon, France.
    Latency-Optimal mmWave Radio Access for V2X Supporting Next Generation Driving Use Cases2019Ingår i: IEEE Access, E-ISSN 2169-3536, Vol. 7, s. 6782-6795Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    With the facilitation of the fifth generation (5G) New Radio (NR), Vehicle-to-Everything (V2X) applications have entered a brand new era to sustain the next generation driving use cases of advanced driving, vehicle platooning, extended sensors and remote driving. To deploy these driving use cases, the service requirements however include low latency, high reliability, and high data rates, which thus render utilizing millimeter wave (mmWave) carriers (spectrum above 6 GHz) as a remedy to empower the next generation driving use cases. However, suffering from severe signal attenuation, transmission range of mmWave carriers may be very limited, which is unfavorable in mobile network deployment to offer seamless services, and compel directional transmission/reception using beamforming mandatory. For this purpose, both a transmitter and a receiver should sweep their beams toward different directions over time, and a communication link can be established only if a transmitter and a receiver arrange their beam directions toward each other at the same time (known as beam alignment). Unfortunately, latency of performing beam sweeping to achieve beam alignment turns out the be a dominating challenge to exploit mmWave, especially for the next generation driving use cases. In this paper, we consequently derive essential principles and designs for beam sweeping at the transmitter side and receivers side, which not only guarantee the occurrence of beam alignment but also optimize the latency to achieve beam alignment. Based on the availabilities of a common geographic reference and the knowledge of beam sweeping scheme at the transmitter side, we derive corresponding performance bounds in terms of latency to achieve beam alignment, and device corresponding latency-optimal beam sweeping schemes. The provided engineering insights therefore pave inevitable foundations to practice the next generation driving use cases using mmWave carriers.

  • 3.
    Parsapoor, Mahboobeh
    et al.
    McGill University, Montreal, QC H3A 2T6, Canada.
    Bilstrup, Urban
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Svensson, Bertil
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Forecasting Solar Activity with Computational Intelligence Models2018Ingår i: IEEE Access, E-ISSN 2169-3536, Vol. 6, s. 70902-70909Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    It is vital to accurately predict solar activity, in order to decrease the plausible damage of electronic equipment in the event of a large high-intensity solar eruption. Recently, we have proposed brain emotional learning-based fuzzy inference system (BELFIS) as a tool for the forecasting of chaotic systems. The structure of BELFIS is designed based on the neural structure of fear conditioning. The function of BELFIS is implemented by assigning adaptive networks to the components of the BELFIS structure. This paper especially focuses on the performance evaluation of BELFIS as a predictor by forecasting solar cycles 16-24. The performance of BELFIS is compared with other computational models used for this purpose, in particular with the adaptive neuro-fuzzy inference system. © 2018 IEEE.

  • 4.
    Xu, Bingyu
    et al.
    Queen Mary University of London, London, United Kingdom.
    Chen, Yue
    Queen Mary University of London, London, United Kingdom.
    Requena Carrión, Jesús
    Queen Mary University of London, London, United Kingdom.
    Loo, Jonathan
    Middlesex University, London, United Kingdom.
    Vinel, Alexey
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Energy-aware Power Control in Energy Cooperation Aided Millimeter Wave Cellular Networks with Renewable Energy Resources2016Ingår i: IEEE Access, E-ISSN 2169-3536, Vol. 5, s. 432-442Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Increased energy consumption becomes a major issue in 5G cellular networks, which inspires the network operators to deploy renewable energy sources. However, due to the fluctuating nature of renewable energy sources, the energy harvested by base stations (BSs) may not fit for their load conditions. The transmit power of the BS needs to be redesigned again. Hence, this paper considers power control in energy cooperation enabled millimeter wave (mmWave) networks, to alleviate the harvested energy imbalance problem and reduce the energy waste. Each BS is solely powered by renewable energy sources and the harvested energy is allowed to be transferred between BSs. Each BS needs to determine whether the energy should be stored in the battery or transferred to others at each time slot. In this work, power control is formulated as a stochastic optimization problem, aiming at maximizing the time average network utility while keeping the network stable. An online algorithm called Dynamic Energy-aware Power Allocation (DEPA) is proposed based on Lyapunov optimization, which does not need to acquire any statistical knowledge of channels and traffic arrivals. Simulation results show that compared with the power control scheme without energy cooperation, the proposed algorithm with energy cooperation can achieve higher network sum rate while reducing the delay and the required battery capacity.

  • 5.
    Zhang, Ke
    et al.
    University of Electronic Science and Technology of China, Chengdu, China.
    Mao, Yuming
    University of Electronic Science and Technology of China, Chengdu, China.
    Leng, Supeng
    University of Electronic Science and Technology of China, Chengdu, China.
    Maharjan, Sabita
    Simula Research Laboratory, Oslo, Norway.
    Zhang, Yan
    Simula Research Laboratory, Oslo, Norway.
    Vinel, Alexey
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Jonsson, Magnus
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Incentive-Driven Energy Trading in the Smart Grid2016Ingår i: IEEE Access, E-ISSN 2169-3536, Vol. 4, s. 1243-1257, artikel-id 7436757Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The smart grid is widely considered as an efficient and intelligent power system. With the aid of communication technologies, the smart grid can enhance the efficiency and reliability of the grid system through intelligent energy management. However, with the development of new energy sources, storage and transmission technologies together with the heterogeneous architecture of the grid network, several new features have been incorporated into the smart grid. These features make the energy trading more complex and pose a significant challenge on designing efficient trading schemes. Based on this motivation, in this paper, we present a comprehensive review of several typical economic incentive approaches adopted in the energy-trading control mechanisms. We focus on the technologies that address the challenges specific to the new features of the smart grid. Furthermore, we investigate the energy trading in a new cloud-based vehicle-to-vehicle energy exchange scenario. We propose an optimal contract-based electricity trading scheme, which efficiently increases the generated profit. © 2013 IEEE.

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