The Experts below are selected from a list of 5112 Experts worldwide ranked by ideXlab platform
Zeljko Pantic - One of the best experts on this subject based on the ideXlab platform.
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analysis design and demonstration of a 25 kw dynamic wireless charging system for roadway electric vehicles
IEEE Journal of Emerging and Selected Topics in Power Electronics, 2018Co-Authors: Reza Tavakoli, Zeljko PanticAbstract:Dynamic wireless charging of electric vehicles (EVs) can significantly extend the EVs’ driving range and consequently, the prospect of electrified transportation. In this paper, a comprehensive study is conducted to elaborate the constraints of real driving conditions and propose a solution that could cope with Misalignment Problem and the dynamics imposed by the charging process and by EVs passing over road-embedded charging pads. A dual-loop primary controller is proposed to regulate primary-side power and current. The controller allows sequential and timely activation of segmented primary coils; it controls the primary coil current at the reference value under no-load and loaded conditions, compensates for power transfer reduction caused by the vehicle lateral Misalignment (LTM), and prevents primary overloading. The primary of the dynamic wireless charger is modeled using the generalized state-space averaging method and the model is verified through simulations and experiments. After that, a controller has been designed and implemented and its operation is evaluated through simulations and experimental tests. A 25-kW charging system with two primary coils is built and tested in a real environment. The measured energy efficiency is 86% for the laterally aligned vehicle, with the possibility to be increased over 90% using enhanced schemes for coils’ activation and deactivation. The system is delivering an equal amount of energy for all LTMs in the range of ±15 cm, which improves the expected value of transferred energy by more than 30%.
Xiaogang Wang - One of the best experts on this subject based on the ideXlab platform.
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ICCV - Person Re-identification by Salience Matching
2013 IEEE International Conference on Computer Vision, 2013Co-Authors: Rui Zhao, Wanli Ouyang, Xiaogang WangAbstract:Human salience is distinctive and reliable information in matching pedestrians across disjoint camera views. In this paper, we exploit the pair wise salience distribution relationship between pedestrian images, and solve the person re-identification Problem by proposing a salience matching strategy. To handle the Misalignment Problem in pedestrian images, patch matching is adopted and patch salience is estimated. Matching patches with inconsistent salience brings penalty. Images of the same person are recognized by minimizing the salience matching cost. Furthermore, our salience matching is tightly integrated with patch matching in a unified structural Rank SVM learning framework. The effectiveness of our approach is validated on the VIPeR dataset and the CUHK Campus dataset. It outperforms the state-of-the-art methods on both datasets.
Rui L. Aguiar - One of the best experts on this subject based on the ideXlab platform.
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Misalignment Problem in matrix decomposition with missing values
Machine Learning, 2021Co-Authors: Sofia Fernandes, Mário Antunes, Diogo Gomes, Rui L. AguiarAbstract:Data collection within a real-world environment may be compromised by several factors such as data-logger malfunctions and communication errors, during which no data is collected. As a consequence, appropriate tools are required to handle the missing values when analysing and processing such data. This Problem is often tackled via matrix decomposition. While it has been successfully applied in a wide range of applications, in this work we report an issue that has been neglected in literature and “degenerates” the quality of the imputations obtained by matrix decomposition in multivariate time-series (with smooth evolution). Briefly, the Problem consists of the Misalignment of the matrix decomposition result: the missing values imputations fall within an incorrect range of values and the transitions between observed and imputed values are not smooth. We address this Problem by proposing a post-processing alignment strategy. According to our experiments, the post-processing adjustment substantially improves the accuracy of the imputations (when the Misalignment occurs). Moreover, the results also suggest that the Misalignment occurs mostly when dealing with a small number of time-series due to lack of generalization ability.
Dan Yang - One of the best experts on this subject based on the ideXlab platform.
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Person Re-Identification by Pose Invariant Deep Metric Learning With Improved Triplet Loss
IEEE Access, 2018Co-Authors: Min Chen, Xin Feng, Dan YangAbstract:Person re-identification (re-ID) is a challenging Problem in the community which aims at identifying person in a surveillance video. Despite recent advance in the field of computer vision, person re-ID still presents great challenge since person’s presence is various under different illumination, viewpoints, occlusion, and background clutter. In this paper, to exploit more discriminative information of person’s appearance, we propose a novel pose invariant deep metric learning (PIDML) method under an improved triplet loss for person re-ID. Our approach contributes the Misalignment Problem and distance metric simultaneously, which are two key Problems for person re-ID. Extensive experiments show that our proposed method could achieve favorable accuracy while compared with the state-of-the-art techniques on the challenging Market-1501, CUHK03, and VIPeR datasets.
Reza Tavakoli - One of the best experts on this subject based on the ideXlab platform.
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analysis design and demonstration of a 25 kw dynamic wireless charging system for roadway electric vehicles
IEEE Journal of Emerging and Selected Topics in Power Electronics, 2018Co-Authors: Reza Tavakoli, Zeljko PanticAbstract:Dynamic wireless charging of electric vehicles (EVs) can significantly extend the EVs’ driving range and consequently, the prospect of electrified transportation. In this paper, a comprehensive study is conducted to elaborate the constraints of real driving conditions and propose a solution that could cope with Misalignment Problem and the dynamics imposed by the charging process and by EVs passing over road-embedded charging pads. A dual-loop primary controller is proposed to regulate primary-side power and current. The controller allows sequential and timely activation of segmented primary coils; it controls the primary coil current at the reference value under no-load and loaded conditions, compensates for power transfer reduction caused by the vehicle lateral Misalignment (LTM), and prevents primary overloading. The primary of the dynamic wireless charger is modeled using the generalized state-space averaging method and the model is verified through simulations and experiments. After that, a controller has been designed and implemented and its operation is evaluated through simulations and experimental tests. A 25-kW charging system with two primary coils is built and tested in a real environment. The measured energy efficiency is 86% for the laterally aligned vehicle, with the possibility to be increased over 90% using enhanced schemes for coils’ activation and deactivation. The system is delivering an equal amount of energy for all LTMs in the range of ±15 cm, which improves the expected value of transferred energy by more than 30%.