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第三届全国智能视觉监控学术会议

作者： Yunhong Wang Zhaoxiang Zhang Yuqing Hou Jie Qin Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital MediaB

ISBN: (纸本)9781457718342

Traffic flow detection plays an important role in intelligent Transportation Systems(ITS).Video based traffic flow detection system is the most widely used strategy in *** this circumstance,we design and implement a video based traffic flow detection system which is called MyTD in this *** takes advantages of both shadow removal and optical flow ***,we introduce the current development of ITS and focus on the video based traffic detection technology,which is the key to ***,a shadow removal algorithm combining information in both RGB and HSV color spaces is ***,based on the Iterative Pyramidal LK Optical Flow Algorithm,a vehicle tracking function is realized by OpenCV,as well as a Connected Components Labeling function and the vehicle counting ***,MyTD is implemented and tested based on the algorithm presented *** results show the outstanding performance of our method comparing with traditional optical flow algorithms.

关键词： Optic Flow Traffic flow Videotapes Detection systems connected component shadows red-green-blue colour model intelligent Tutoring Systems intelligent transportation systems

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Dynamic Graph Dismantling with Reinforcement Supervised Learning 42

Dynamic Graph Dismantling with Reinforcement Supervised Lear...

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42nd Chinese Control Conference, CCC 2023

作者： Wang, Yumei Tang, Chuancong Zhang, Hai-Tao School of Artificial Intelligence and Automation Huazhong University of Science and Technology The Engineering Research Center of Autonomous Intelligent Unmanned Systems The Key Laboratory of Image Processing and Intelligent Control The State Key Laboratory of Digital Manufacturing Equipment and Technology Wuhan430074 China

ISBN: (纸本)9789887581543

There are always some 'key' nodes in a big complex network, which can joint the most connected subgraphs. How to identify these nodes, finding a minimum set of nodes to attack for reducing the size of residual network's Largest Connected Component(LCC) to break up the original network, has become a research hotspot. Therefore, a method for determining the 'key' nodes based on reinforcement learning framework and supervised learning model is proposed. This algorithm can not only utilize the dynamic exploration ability of reinforcement learning to collect a rich training dataset, but also take advantage of the characteristics that supervised learning is adaptive and has strong generalization ability to possess high efficiency and strong robustness. In order to further improve the algorithm's performance, ϵ-greedy mechanism is used to explore more network states. The experiment results show that given the same fraction of removed nodes, our algorithm can make the residual LCC smaller in various networks which is superior to the state-of-the-art algorithms in terms of effectiveness and generalization. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Complex networks

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WDNet: A Water Depth Perception Network with Global Information 42

WDNet: A Water Depth Perception Network with Global Informat...

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42nd Chinese Control Conference, CCC 2023

作者： Huang, Zhihui Tang, Yifeng Tang, Chuancong Xu, Yifan Luo, Chuanshang Liu, Bin Zhang, Hai-Tao School of Artificial Intelligence and Automation The Engineering Research Center of Autonomous Intelligent Unmanned Systems The Key Laboratory of Image Processing and Intelligent Control The State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9789887581543

Deep perception of the unmanned surface vehicle's surroundings is an inaccessible part of its fully autonomous navigation mission. The existing methods, whether based on traditional stereo matching or deep learning, do not fully consider the characteristics of water environment, resulting in severe error depths in weak textures (sky, calm lake) and water reflections regions, that increases the risk of running aground or collision. What is worse that there is not a public dataset for depth estimation in the water environment. Therefore, this work proposes a self-supervised model for depth estimation named Water Depth Perception Network (WDNet) to address these problems. The decoder of this network has a wider receptive field and can effectively handle the depth error in the weak texture region. Besides, the WDNet is trained with a novel and effective loss function which assist the network to reduce errors in sky and water region, and some indexes are proposed to evaluate the model's performances in sky and water region. Finally, our proposed WDNet achieves a 0.1056 absolute relative error in ranging, the average number of error pixels in the sky area drops from 15803.87 to 580.91, which only accounted for 0.29% of the image, and the error in water region drops from 51.04 to 6.75, all of them are superior to the performance of baseline model. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Errors

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New method for improving the performance of SAR image segmentation

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Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology 2011年第7期33卷 1700-1705页

作者： Yan, Xue-Ying Jiao, Li-Cheng Wang, Ling-Xia Wan, Hong-Lin Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

Considering the shortage of edge preservation and low direction-resolution for SAR image segmentation based on the conventional wavelet transform domain, a new segmentation method is proposed based on Gray-Level Cooccurrence Probability (GLCP) features in the overcomplete Brushlet domain. This method compresses the redundant GLCP features extracted by the adaptive window Gabor filtering in different direction coefficient blocks using compressed sensing, then the Fuzzy C-Mean (FCM) clustering method is utilized to complete the clustering and obtain the segmentation result. The experiment results show that the new method has advantages in the edge preservation and direction extraction, and obtains better segmentation results with respect to other methods.

关键词： Gabor filters

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Neuronal population dynamic model: An analytic approach

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Progress in Natural Science:Materials International 2009年第9期19卷 1159-1163页

作者： Wentao Huang a, Licheng Jiao a, Yuelei Xub, Shiping Ma b, Jianhua Jia a a Institute of intelligent Information processing, key laboratory of intelligent Perception and image Understanding of Ministry of Education, Xidian University, P.O. Box 224, Xi’an 710071, China b Department of Avionics Engineering, Engineering College of Air Force Engineering University, Xi’an 710038, China [a]Institute of Intelligent Information Processing Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Xidian University P.O. Box 224 Xi’an 710071 China [b]Department of Avionics Engineering Engineering College of Air Force Engineering University Xi’an 710038 China

A novel analytic approach is presented to study the population of excitatory and inhibitory spiking neurons in this paper. The evolution in time of the population dynamic equation is determined by a partial differential equation. A new function is proposed to characterize the population of excitatory and inhibitory spiking neurons, which is different from the population density function discussed by most researchers. And a novel evolution equation, which is a nonhomogeneous parabolic type equation, is derived. From this, the stationary solution and the firing rate of the stationary states are given. Last, by the Fourier transform, the time dependent solution is also obtained. This method can be used to analyze the various dynamic behaviors of neuronal populations.

关键词： Analytic approach Neuronal population Dynamic model Fourier transform

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An Online Ascent Phase Trajectory Reconstruction Algorithm Using Gauss Pseudospectral Method

An Online Ascent Phase Trajectory Reconstruction Algorithm U...

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2012 International Conference on Modelling,Identification and Control(建模、辨别与控制国际会议 ICMIC 2012)

作者： Da Zhang Xuefang Lu YongJi Wang Lei Liu Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Department of C Key Laboratory of Ministry of Education for Image Processing and Intelligent ControlDepartment of Co

ISBN: (纸本)9781467315241

In this paper, we present an online ascent phase trajectory reconstruction algorithm using Gauss Pseudospectral *** Pseudospectral Method (GPM) was used to transform the ascent phase trajectory optimization problem into Nonlinear Program Problem (NLP), we solve the problem using a optimization software named GPOPS in *** this method we can calculate the optimal trajectory control volume and feedback to update the guidance commands *** analysis of the optimized results has been done to prove its *** last, we compare the trajectory recon- struction algorithm to a law without reconstruction algorithm via simulation with aerodynamic and thrust *** simulation results indicate that the method proposed above offers improved performance and has ability for real-time calculating.

关键词： Ascent Phase Trajectory Online Trajectory Reconstruction Gauss Pseudospectral Method Nonlinear Pro- gramming

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Texture classification based on mapping complex directionlet

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Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology 2009年第6期31卷 1332-1336页

作者： Bai, Jing Jia, Jian-Hua Jiao, Li-Cheng Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xi'an 710071 China

Directionlet transform can capture the image singularity due to possessing the multi-direction anisotropic basis functions. A texture classification algorithm based on the Mapping complex Directionlet Transform (M-DT) is proposed, which provides better directionality and approximate shift invariance. By space mapping for the texture image, then complex Directionlet transform is applied to the mapped image, and the multiscale subband coefficient energy feature is used for texture classification. The experiments using texture images from Brodatz and real SAR images indicate the proposed method outperforms wavelets and Multiscale Geometric Analysis (MGA) approaches, the potential application to image analysis by Directionlet is thus proved.

关键词： Synthetic aperture radar

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Hyperspectral image compression using distributed source coding and 3D-SPECK

Hyperspectral image compression using distributed source cod...

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MIPPR 2009 - Multispectral image Acquisition and processing: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Wu, Jiaji Jiang, Kun Fang, Yong Jiao, Licheng Shi, Guangming Key Laboratory of Intelligent Perception and Image Understanding Institute of Intelligent Information Processing Xidian University Xi'an 710071 China College of Information Engineering Northwest A and F University Shaanxi Yangling 712100 China

ISBN: (纸本)9780819478054

In this paper, we propose a method based on both 3D-SPECK (3D Set Partitioning Embedded Block) and the theory of DSC (Distributed Source Coding) to realize the compression of hyperspectral images. Some experiments have been done to evaluate the compression performance, and the experimental results show that our methods can get competitive performance than 3D-SPECK, 3D-SPIHT. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： image compression

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Multi-agent containment control with input saturation on switching topologies

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IET Control Theory and Applications 2015年第3期9卷 399-409页

作者： Su, Housheng Chen, Michael A.Q. School of Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Luoyu Road 1037 Wuhan430074 China Department of Mechanical Engineering University of Hong Kong Hong Kong Hong Kong

This study aims to investigate containment control of linear multi-agent systems with input saturation on switching topologies. For such a multi-agent system, both state feedback and output feedback containment control protocols are proposed via a novel low-gain feedback approach. Consequently, the authors show that, under the assumption that the switching networks are jointly connected, semi-global state feedback and output feedback containment control of the multi-agent system can be attained. The effectiveness of the proposed algorithms is illustrated via numerical examples. © 2015 The Institution of Engineering and Technology.

关键词： Multi agent systems

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A topic relevance-aware click model for web search

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Journal of intelligent and Fuzzy Systems 2024年第4期46卷 8961-8974页

作者： Jianping, Liu Yingfei, Wang Jian, Wang Meng, Wang Xintao, Chu College of Computer Science and Engineering North Minzu University Yinchuan China The Key Laboratory of Images Graphics Intelligent Processing of State Ethnic Affairs Commission North Minzu University Yinchuan China Agricultural Information Institute Chinese Academy of Agricultural Sciences Beijing China

To better understand users’ behavior patterns in web search, numerous click models are proposed to extract the implicit interaction feedback. Most existing click models are heavily based on the implicit information to model user behaviors, ignoring the impact of explicit information between queries and documents in search sessions. In this paper, we fully consider the topic relevance between queries and documents in search sessions and propose a novel topic relevance-aware click model (TRA-CM) for web search. TRA-CM consists of a relevance estimator and an examination predictor. The relevance estimator consists of a topic relevance predictor and a click context encoder. In the topic relevance predictor, we utilize the pre-trained BERT model to model the content information of queries and documents in search sessions. Meanwhile, we use transformer to encode users’ click behaviors in the click context encoder. We further apply a two-stage fusion strategy to obtain the final relevance scores. The examination predictor estimates the examination probability of each document. We further utilize learnable filters to attenuate log noise and obtain purer input features in both relevance estimator and examination predictor, and investigate different combination functions to integrate relevance scores and examination probabilities into click prediction. Extensive experiment results on two real-world session datasets prove that TRA-CM outperforms existing click models in both click prediction and relevance estimation tasks. © 2024 – IOS Press. All rights reserved.

关键词： Forecasting

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