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arXiv 2021年

作者： Jin, Yu Zhang, Jiayi Huang, Chongwen Yang, Liang Xiao, Huahua Ai, Bo Wang, Zhiqin The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong University Beijing100044 China Zhejiang Provincial Key Lab of Information Processing Communication and Networking Zhejiang University Hangzhou310007 China College of Computer Science and Electronic Engineering Hunan University Changsha410082 China ZTE Corporation State Key Laboratory of Mobile Network Mobile Multimedia Technology Shenzhen518057 China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou University Zhengzhou450001 China Research Center of Networks and Communications Peng Cheng Laboratory Shenzhen518055 China China Academy of Information and Communications Technology Beijing100191 China

Reconfigurable intelligent surface (RIS) constitutes an essential and promising paradigm that relies programmable wireless environment and provides capability for space-intensive communications, due to the use of low-cost massive reflecting elements over the entire surfaces of man-made structures. However, accurate channel estimation is a fundamental technical prerequisite to achieve the huge performance gains from RIS. By leveraging the low rank structure of RIS channels, three practical residual neural networks, named convolutional blind denoising network, convolutional denoising generative adversarial networks and multiple residual dense network, are proposed to obtain accurate channel state information, which can reflect the impact of different methods on the estimation performance. Simulation results reveal the evolution direction of these three methods and reveal their superior performance compared with existing benchmark schemes. Copyright © 2021, The Authors. All rights reserved.

关键词： Channel estimation

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Re-ID driven localization refinement for person search

arXiv

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arXiv 2019年

作者： Han, Chuchu Ye, Jiacheng Zhong, Yunshan Tan, Xin Zhang, Chi Gao, Changxin Sang, Nong Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Peking University Shanghai Jiao Tong University Megvii Technology

Person search aims at localizing and identifying a query person from a gallery of uncropped scene images. Different from person re-identification (re-ID), its performance also depends on the localization accuracy of a pedestrian detector. The state-of-the-art methods train the detector individually, and the detected bounding boxes may be suboptimal for the following re-ID task. To alleviate this issue, we propose a re-ID driven localization refinement framework for providing the refined detection boxes for person search. Specifically, we develop a differentiable ROI transform layer to effectively transform the bounding boxes from the original images. Thus, the box coordinates can be supervised by the re-ID training other than the original detection task. With this supervision, the detector can generate more reliable bounding boxes, and the downstream re-ID model can produce more discriminative embeddings based on the refined person localizations. Extensive experimental results on the widely used benchmarks demonstrate that our proposed method performs favorably against the state-of-the-art person search methods. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

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Predefined-time terminal sliding mode control of robot manipulators

arXiv

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arXiv 2020年

作者： Liang, Chang-Duo Ge, Ming-Feng Liu, Zhi-Wei Wang, Yan-Wu Karimi, Hamid Reza School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan430074 China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Image Processing and Intelligent Control Ministry of Education Huazhong University of Science and Technology Wuhan430074 China Department of Mechanical Engineering Politecnico di Milano Milan20156 Italy

In this paper, we present a new terminal sliding mode control to achieve predefined-time stability of robot manipulators. The proposed control is developed based on a novel predefined-time terminal sliding mode (PTSM) surface, on which the states are forced to reach the origin in a predefined time, i.e., the settling time is independent to the initial condition and can be explicitly user-defined via adjusting some specific parameters called the predefined-time parameters. It is also demonstrated that the proposed control can provide satisfactory steady-state performance in the case of both external disturbances and parametric uncertainties. Besides, we present a formal systemic analysis method to derive the sufficient conditions for guaranteeing the predefined-time convergence of the closed-loop system. Finally, the effectiveness and performance of the presented control scheme are illustrated through both theoretical comparisons and numerical simulations. Copyright © 2020, The Authors. All rights reserved.

关键词： Sliding mode control

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Finite-size scaling of geometric renormalization flows in complex networks

arXiv

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arXiv 2020年

作者： Chen, Dan Su, Housheng Wang, Xiaofan Pan, Gui-Jun Chen, Guanrong School of Artificial Intelligence and Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan430074 China Department of Automation Shanghai University Shanghai200072 China Faculty of Physics and Electronic Science Hubei University Wuhan430062 China Department of Electrical Engineering City University of Hong Kong Hong Kong Hong Kong

Recently, the concept of geometric renormalization group provides a good approach for studying the structural symmetry and functional invariance of complex networks. Along this line, we systematically investigate the finite-size scaling of structural and dynamical observables in geometric renormalization flows of synthetic and real evolutionary networks. Our results show that these observables can be well characterized by a certain scaling function. Specifically, we show that the critical exponent implied by the scaling function is independent of these observables but only depends on the small-world properties of the network, namely, all networks located in the small-world phase have a uniform scaling exponent, while those located in the non-small-world phase and in their critical regions have another uniform scaling. More importantly, we perform extensive experiments on real evolutionary networks with small-world characteristics, and our results show that these observables also have uniform scaling in their geometric renormalization flows. Therefore, in a sense this exponent can be used as an effective measure for classifying universal small-world and non-small-world network models. © 2020, CC BY-SA.

关键词： Geometry

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Development of an MEMS based biomimetic whisker sensor for tactile sensing

Development of an MEMS based biomimetic whisker sensor for t...

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IEEE International Conference on Cyborg and Bionic Systems (CBS)

作者： Zihou Wei Qing Shi Chang Li Shurui Yan Guanglu Jia Zhigang Zeng Qiang Huang Toshio Fukuda Key Laboratory of Biomimetic Robots and Systems Key Laboratory of Biomimetic Robots and Systems (Beijing Institute of Technology) Ministry of Education Beijing China Key Laboratory of Ministry of Education for Image Processing and Intelligent Control the School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9781728150734

ISBN: (纸本)9781728150741

It has been demonstrated that biological whisker sensing system has excellent capacity to achieve the pattern recognition, and whisker sensor based robot tactile perception has caused widespread concern. However, most of current existed whisker sensors are too large in size, and are difficult to be integrated into a small robot. In this paper, we proposed a MEMS based biomimetic whisker sensor inspired by rats, which integrates four sensing units on a square silicon wafer with a side length of 6.8mm and makes it possible to be installed on a small robot with similar size to a real rat. Our sensor measure the bending moment at the root of the whisker based on the piezoresistive effect. We have explored the range of functions that whisker arrays can serve on and it is shown that our whisker sensor can determine obstacle distance, and is also capable of gathering surface information including shape and texture.

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Automatic Monitoring of Driver's Physiological Parameters Based on Microarray Camera

Automatic Monitoring of Driver's Physiological Parameters Ba...

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IEEE Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS)

作者： Jiancheng Zou Zhengzheng Li Peizhou Yan Institute of Image Processing and Pattern Recognition North China University of Technology Beijing Key Laboratory of Urban Rod Traffic Intelligent Control Technology North China University of Technology Shijingshan District Beijing China

Driver's physical and mental states are very important factors affecting the driving states. Traffic accidents are occurred by accompanying abnormal physiological parameters. So how to monitor automatically driver's physiological parameters is an important problem. A real-time driver's physiological parameters monitoring method based on microarray camera is proposed in this paper. Firstly, we use a microarray camera to acquire videos in real time without contact. Secondly, the videos are registered and fused into a high quality video. Thirdly, deep learning framework is used to capture driver's facial data quickly. Then based on the principle of imaging photoplethysmography (IPPG) algorithm, physiological parameters such as heart rate (HR) and oxygen saturation (SpO 2 ) are monitored in real time. Results of expression analysis can further support the physiological parameters monitoring results. The experimental results show that the method proposed in this paper can monitor the physiological parameters of drivers in real time and accurately, and it is hopeful to play an active role in improving traffic safety.

关键词： Biomedical monitoring Monitoring Cameras Videos Heart rate Real-time systems

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Multiple phase transitions in networks of directed networks

引用

Physical Review E 2019年第1期99卷 012312-012312页

作者： Xueming Liu Linqiang Pan H. Eugene Stanley Jianxi Gao Key Laboratory of Image Information Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan 430074 Hubei China Department of Physics Center for Polymer Studies Boston University Boston Massachusetts 02215 USA Department of Computer Science Rensselaer Polytechnic Institute Troy New York 12180 USA

The robustness in real-world complex systems with dependency connectivities differs from that in isolated networks. Although most complex network research has focused on interdependent undirected systems, many real-world networks—such as gene regulatory networks and traffic networks—are directed. We thus develop an analytical framework for examining the robustness of networks made up of directed networks of differing topologies. We use it to predict the phase transitions that occur during node failures and to generate the phase diagrams of a number of different systems, including treelike and random regular (RR) networks of directed Erdős-Rényi (ER) networks and scale-free networks. We find that the the phase transition and phase diagram of networks of directed networks differ from those of networks of undirected networks. For example, the RR networks of directed ER networks show a hybrid phase transition that does not occur in networks of undirected ER networks. In addition, system robustness is affected by network topology in networks of directed networks. As coupling strength q increases, treelike networks of directed ER networks change from a second-order phase transition to a first-order phase transition, and RR networks of directed ER networks change from a second-order phase transition to a hybrid phase transition, then to a first-order phase transition, and finally to a region of collapse. We also find that heterogenous network systems are more robust than homogeneous network systems. We note that there are multiple phase transitions and triple points in the phase diagram of RR networks of directed networks and this helps us understand how to increase network robustness when designing interdependent infrastructure systems.

关键词： Attacks on networks Cascades Continuous phase transition Discontinuous phase transition Network phase transitions Percolation phase transition Random attacks Robustness Topological phase transition

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TSW-FD: A Novel Temporal and Spatial Domain Weight Analysis of Feature Difference for Micro-Expression Spotting

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Journal of Physics: Conference Series 2021年第1期1828卷

作者： Zhihao Zhang Fan Mo Ke Zhao Tong Chen Xiaolan Fu State Key Laboratory of Brain and Cognitive Science Institute of Psychology Chinese Academy of Sciences Beijing 100101 China Department of Psychology University of Chinese Academy of Sciences Beijing 100049 China Chongqing Key Laboratory of Non-linear Circuit and Intelligent Information Processing Southwest University Chongqing 400715 China Chongqing Key Laboratory of Artificial Intelligence and Service Robot Control Technology Chongqing 400715 China

The micro-expression spotting has recently attracted increasing attention from psychology and computer vision community, since embraced in the second facial Micro-Expression Grand Challenge (MEGC 2019). Different from the original feature difference (FD) analysis, in this paper, we proposed a novel temporal and spatial domain weight analysis of feature difference (TSW-FD) to achieve micro-expression spotting. The experimental results showed that TSW-FD improved 17.86% and 24.21% in F1-Score comparing to the FD in CASME II and SMIC-E-HS.

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$H_{\infty}$ consensus control of fractional-order multi-agent systems over the directed graph

$H_{\infty}$ consensus control of fractional-order multi-age...

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Chinese control Conference (CCC)

作者： Lin Chen Wen-Sen Wang Hao Wu Yan Lei Jiang-Wen Xiao Key Laboratory of Image Processing and Intelligent Control Ministry of Education State grid shanxi electric power research institute

In this paper, the H ∞ consensus of fractional-order multi-agent systems with directed communication graph is investigated. It's the first time to introduce the H ∞ control to investigate the consensus problem of the fractional-order multi-agent systems. In view of Mittag-Leffler stability theory and fractional Lyapunov directed method, a sufficient condition is presented to guarantee all the agents reach consensus with the desired H ∞ performance. Finally, the results are verified by several numerical simulations.

关键词： Multi-agent systems control systems Laplace equations Eigenvalues and eigenfunctions Power system stability Stability analysis Graph theory

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Multi-task deep learning with dynamic programming for embryo early development stage classification from time-lapse videos

arXiv

引用

arXiv 2019年

作者： Liu, Zihan Huang, Bo Cui, Yuqi Xu, Yifan Zhang, Bo Zhu, Lixia Wang, Yang Jin, Lei Wu, Dongrui Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Reproductive Medicine Center Huazhong University of Science and Technology Tongji Hospital Wuhan430074 China

Time-lapse is a technology used to record the development of embryos during in-vitro fertilization (IVF). Accurate classification of embryo early development stages can provide embryologists valuable information for assessing the embryo quality, and hence is critical to the success of IVF. This paper proposes a multi-task deep learning with dynamic programming (MTDL-DP) approach for this purpose. It first uses MTDL to pre-classify each frame in the time-lapse video to an embryo development stage, and then DP to optimize the stage sequence so that the stage number is monotonically non-decreasing, which usually holds in practice. Different MTDL frameworks, e.g., oneto-many, many-to-one, and many-to-many, are investigated. It is shown that the one-to-many MTDL framework achieved the best compromise between performance and computational cost. To our knowledge, this is the first study that applies MTDL to embryo early development stage classification from time-lapse videos. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep learning

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