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Face detection and recognition based on deep learning in the monitoring environment 4th

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Face detection and recognition based on deep learning in the...

4th International Conference of Pioneer computer Scientists, Engineers and Educators, ICPCSEE 2018

作者： Zhu, Chaoping Yang, Yi School of Computer Science and Information Engineering Chongqing Technology and Business University Chongqing400067 China Detection and Control of Integrated Systems Engineering Laboratory Chongqing400076 China

ISBN: (纸本)9789811322020

In the construction of smart cities and public safety, the number of cameras has increased dramatically, the artificial video management cannot meet the demand of urban construction. Therefore, intelligent video monitoring technology has become a research hotspot. In the actual video monitoring,the monitoring environment is very complex, Face recognition in video is often difficulty. This paper research the face recognition problem of monitoring video in the city, propose a mothed of detection and recognition method based on deep learning. The detection part adopts the fast speeding YOLO2 algorithm, the recognition part adopts high accuracy ResNet algorithm. Using WIDERFACE face detection database as training data set, Use the CASIA_Webface database for validation experiments. The experimental data show that the mothod YOLO2 algorithm and ResNet algorithm can complete detection and recognition of human face in monitoring video. the result is better. To further verify the recognition effect, the data set collected by the actual camera was tested. the test results show that the real time and accuracy of the system can meet the needs of practical engineering application. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Face recognition

Nonlinear Virtual Inertia control of WTGs for Enhancing Primary Frequency Response and Suppressing Drive-Train Torsional Oscillations

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arXiv 2020年

作者： Liu, Bi Huang, Qi Zhao, Junbo Milano, Federico Zhang, Yingchen Sichuan Provincial Key Lab of Power System Wide-area Measurement and Control University of Electronic Science and Technology of China Chengdu Sichuan611731 China Department of Electrical and Computer Engineering Mississippi State University StarkvilleMS39762 United States School of Electrical and Electronic Engineering University College Dublin Dublin Ireland National Renewable Energy Laboratory GoldenCO80401 United States

Virtual inertia controllers (VICs) for wind turbine generators (WTGs) have been recently developed to compensate the reduction of inertia in power systems. However, VICs can induce low frequency torsional oscillations of the drive train of WTGs. This paper addresses this issue and develops a new nonlinear VIC based on objective holographic feedbacks theory. This approach allows transforming the original nonlinear control into a completely controllable system of Brunovsky’s type. Simulation results under various scenarios demonstrate that the proposed method outperforms existing VICs in terms of suppression of low frequency drive-train torsional oscillations, enhancement of system frequency nadir as well as fast and smooth recovery of WTG rotor speed to the original MPP point before the disturbance. The proposed method is also able to coordinate multiple WTGs. Copyright © 2020, The Authors. All rights reserved.

关键词： Frequency response

Bayesian model selection for change point detection and clustering

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arXiv 2019年

作者： Mazhar, Othmane Rojas, Cristian R. Fischione, Carlo Hesamzadeh, Mohammad R. Division of Decision And Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology StockholmSE-100 44 Sweden Division of Network And Sytems Engineering School of Electrical Engineering and Computer Science KTH Royal Institute of Technology StockholmSE-100 44 Sweden Division of Electric Power And Energy Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology StockholmSE-100 44 Sweden

We address the new problem of estimating a piece-wise constant signal with the purpose of detecting its change points and the levels of clusters. Our approach is to model it as a nonparametric penalized least square model selection on a family of models indexed over the collection of partitions of the design points and propose a computationally efficient algorithm to approximately solve it. Statistically, minimizing such a penalized criterion yields an approximation to the maximum a-posteriori probability (MAP) estimator. The criterion is then analyzed and an oracle inequality is derived using a Gaussian concentration inequality. The oracle inequality is used to derive on one hand conditions for consistency and on the other hand an adaptive upper bound on the expected square risk of the estimator, which statistically motivates our approximation. Finally, we apply our algorithm to simulated data to experimentally validate the statistical guarantees and illustrate its behavior. Copyright © 2019, The Authors. All rights reserved.

关键词： Least squares approximations

Reflecting modulation

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arXiv 2019年

作者： Guo, Shuaishuai Lv, Shuheng Zhang, Haixia Ye, Jia Zhang, Peng Shandong Provincial Key Laboratory of Wireless Communication Technologies School of Control Science and Engineering Shandong University Jinan250061 China Thuwal23955-6900 Saudi Arabia School of Computer Engineering Weifang University Weifang261061 China

Reconfigurable intelligent surface (RIS) has emerged as a promising technique for future wireless communication networks. How to reliably transmit information in a RIS-based communication system arouses much interest. This paper proposes a reflecting modulation (RM) scheme for RIS-based communications, where both the reflecting patterns and transmit signals can carry information. Depending on that the transmitter and RIS jointly or independently deliver information, RM is further classified into two categories: jointly mapped RM (JRM) and separately mapped RM (SRM). JRM and SRM are naturally superior to existing schemes, because the transmit signal vectors, reflecting patterns, and bit mapping methods of JRM and SRM are more flexibly designed. To enhance transmission reliability, this paper proposes a discrete optimization-based joint signal mapping, shaping, and reflecting (DJMSR) design for JRM and SRM to minimize the bit error rate (BER) with a given transmit signal candidate set and a given reflecting pattern candidate set. To further improve the performance, this paper optimizes multiple reflecting patterns and their associated transmit signal sets in continuous fields for JRM and SRM. Numerical results show that JRM and SRM with the proposed system optimization methods considerably outperform existing schemes in BER. Copyright © 2019, The Authors. All rights reserved.

关键词： Bit error rate

Spatial and temporal consistency-aware dynamic adaptive streaming for 360-degree videos

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arXiv 2019年

作者： Yuan, Hui Zhao, Shiyun Hou, Junhui Wei, Xuekai Kwong, Sam School of Control Science and Engineering Shandong University Ji’nan250061 China School of Information Science and Engineering Shandong University Qingdao266237 China Department of Computer Science City University of Hong Kong Kowloon Hong Kong

The 360-degree video allows users to enjoy the whole scene by interactively switching viewports. However, the huge data volume of the 360-degree video limits its remote applications via network. To provide high quality of experience (QoE) for remote web users, this paper presents a tile-based adaptive streaming method for 360-degree videos. First, we propose a simple yet effective rate adaptation algorithm to determine the requested bitrate for downloading the current video segment by considering the balance between the buffer length and video quality. Then, we propose to use a Gaussian model to predict the field of view at the beginning of each requested video segment. To deal with the circumstance that the view angle is switched during the display of a video segment, we propose to download all the tiles in the 360-degree video with different priorities based on a Zipf model. Finally, in order to allocate bitrates for all the tiles, a two-stage optimization algorithm is proposed to preserve the quality of tiles in FoV and guarantee the spatial and temporal smoothness. Experimental results demonstrate the effectiveness and advantage of the proposed method compared with the state-of-the-art methods. That is, our method preserves both the quality and the smoothness of tiles in FoV, thus providing the best QoE for users. Copyright © 2019, The Authors. All rights reserved.

关键词： Quality of service

An ensemble rate adaptation framework for dynamic adaptive streaming over HTTP

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arXiv 2019年

作者： Yuan, Hui Hu, Xiaoqian Hou, Junhui Wei, Xuekai Kwong, Sam School of Control Science and Engineering Shandong University Ji’nan250061 China School of Information Science and Engineering Shandong University Qingdao266237 China Department of Computer Science City University of Hong Kong Kowloon Hong Kong

—Rate adaptation is one of the most important issues in dynamic adaptive streaming over HTTP (DASH). Due to the frequent fluctuations of the network bandwidth and complex variations of video content, it is difficult to deal with the varying network conditions and video content perfectly by using a single rate adaptation method. In this paper, we propose an ensemble rate adaptation framework for DASH, which aims to leverage the advantages of multiple methods involved in the framework to improve the quality of experience (QoE) of users. The proposed framework is simple yet very effective. Specifically, the proposed framework is composed of two modules, i.e. the method pool and method controller. In the method pool, several rate adaptation methods are integrated. At each decision time, only the method that can achieve the best QoE is chosen to determine the bitrate of the requested video segment. Besides, we also propose two strategies for switching methods, i.e., InstAnt Method Switching, and InterMittent Method Switching, for the method controller to determine which method can provide the best QoEs. Simulation results demonstrate that, the proposed framework always achieves the highest QoE for the change of channel environment and video complexity, compared with state-of-the-art rate adaptation methods. Copyright © 2019, The Authors. All rights reserved.

关键词： Quality of service

Modal regression based structured low-rank matrix recovery for multi-view learning

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arXiv 2020年

作者： Xu, Jiamiao Wang, Fangzhao Peng, Qinmu You, Xinge Wang, Shuo Jing, Xiao-Yuan Philip Chen, C.L. School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan430074 China Shenzhen Huazhong University of Science and Technology Research Institute China State Key Laboratory of Software Engineering School of Computer Wuhan University China Department of Computer and Information Science Faculty of Science and Technology University of Macau 99999 China Dalian Maritime University Dalian116026 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100080 China

Low-rank Multi-view Subspace Learning (LMvSL) has shown great potential in cross-view classification in recent years. Despite their empirical success, existing LMvSL based methods are incapable of well handling view discrepancy and discriminancy simultaneously, which thus leads to the performance degradation when there is a large discrepancy among multi-view data. To circumvent this drawback, motivated by the block-diagonal representation learning, we propose Structured Low-rank Matrix Recovery (SLMR), a unique method of effectively removing view discrepancy and improving discriminancy through the recovery of structured low-rank matrix. Furthermore, recent low-rank modeling provides a satisfactory solution to address data contaminated by predefined assumptions of noise distribution, such as Gaussian or Laplacian distribution. However, these models are not practical since complicated noise in practice may violate those assumptions and the distribution is generally unknown in advance. To alleviate such limitation, modal regression is elegantly incorporated into the framework of SLMR (term it MR-SLMR). Different from previous LMvSL based methods, our MR-SLMR can handle any zero-mode noise variable that contains a wide range of noise, such as Gaussian noise, random noise and outliers. The alternating direction method of multipliers (ADMM) framework and half-quadratic theory are used to efficiently optimize MR-SLMR. Experimental results on four public databases demonstrate the superiority of MR-SLMR and its robustness to complicated noise. Copyright © 2020, The Authors. All rights reserved.

关键词： Gaussian noise (electronic)

Limitations on sharing bell nonlocality between sequential pairs of observers

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arXiv 2021年

作者： Cheng, Shuming Liu, Lijun Baker, Travis J. Hall, Michael J.W. The Department of Control Science and Engineering Tongji University Shanghai201804 China Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai201804 China Institute for Advanced Study Tongji University Shanghai200092 China College of Mathematics and Computer Science Shanxi Normal University Linfen041000 China Centre for Quantum Computation and Communication Technology Australian Research Council Centre for Quantum Dynamics Griffith University BrisbaneQLD4111 Australia Department of Theoretical Physics Research School of Physics Australian National University CanberraACT0200 Australia

We give strong analytic and numerical evidence that, under mild measurement assumptions, two qubits cannot both be recycled to generate Bell nonlocality between multiple independent observers on each side. This is surprising, as under the same assumptions it is possible to recycle just one of the qubits an arbitrarily large number of times [P. J. Brown and R. Colbeck, Phys. Rev. Lett. 125, 090401 (2020)]. We derive corresponding 'one-sided monogamy relations' that rule out two-sided recycling for a wide range of parameters, based on a general tradeoff relation between the strengths and maximum reversibilities of qubit measurements. We also show if the assumptions are relaxed to allow sufficiently biased measurement selections, then there is a narrow range of measurement strengths that allows two-sided recycling for two observers on each side, and propose an experimental test. Our methods may be readily applied to other types of quantum correlations, such as steering and entanglement, and hence to general information protocols involving sequential measurements. Copyright © 2021, The Authors. All rights reserved.

关键词： Recycling

String Stability control Strategy Analysis of Mixed Traffic Flow with the CIVs and NCVs

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Journal of Physics: Conference Series 2021年第1期2025卷

作者： Junjie Zhang Can Yang Haiyang Yu Jun Zhang Zixiao Wang Hefei Innovation Research Institute Beihang University Hefei China Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control School of Transportation Science and Engineering Beihang University Beijing China School of Computer Science and Technology Anhui University Hefei China

With the development of vehicle-to-infrastructure cooperation system, a mixed traffic phenomenon with non-connected vehicles (NCVs) and connected and intelligent vehicles (CIVs) will exist over a long period of time. Therefore, the mixed traffic flow stability control has become a hot topic in the future. In order to improve the string stability in the complex and changeable internet of vehicles environment, it is necessary to propose the optimal control method of string stability in the mixed traffic flow. In this paper, NCV and CIV car-following modes are employed to propose a local platoon control method of the connected vehicle, which can achieve the purpose of optimizing the mixed traffic flow stability. Two types of local mixed platoon are considered when the effective communication distance with two vehicles in the vehicle-to-vehicle (V2V) communication. Numerical simulations results show that our proposed string stability control strategy has the effectiveness in the improvement of the mixed traffic flow stability.

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