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Consensus in second-order multi-agent systems via impulsive control using position-only information with heterogeneous delays

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IET Control Theory and Applications 2015年第3期9卷 336-345页

作者： Wang, Yan-Wu Yi, Jing-Wen School of Automation Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science AndTechnology Ministry of China China

This study investigates the consensus problem of second-order multi-agent systems (MASs) via impulsive control using position-only information with communication delays. The communication delays between any two distinct agents are different which can be larger than one impulsive period. A distributed impulsive consensus protocol is designed, in which only the delayed sampled relative positions to neighbours and the relative position to the last sampling state are utilised. By introducing some virtual subgraphs and performing three steps of model transformation, the consensus problem of original continuous-time system is converted to the stability problem of a discrete-time expanded error system. Some necessary and sufficient criteria are derived to grantee the dynamic average-consensus of the MAS. Furthermore, a special case, that is, the delays less than one impulsive period, is discussed, and the bounds of impulsive periods for the dynamic average-consensus are obtained in explicit expressions for both the undirected and directed communication graphs, respectively. Two numerical simulation examples are given to illustrate the effectiveness of theoretical results. © 2015 The Institution of Engineering and Technology.

关键词： Multi agent systems

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An effective crowd property analysis system for video surveillance application 13th

An effective crowd property analysis system for video survei...

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13th International Forum of Digital TV and Wireless Multimedia communication, IFTC 2016

作者： Yang, Shuying Yang, Hua Li, Jijia Zhu, Ji Institute of Image Communication and Network Engineering Shanghai Jiao Tong University Shanghai China Shanghai Key Laboratory of Digital Media Processing and Transmission Shanghai China

ISBN: (纸本)9789811042102

For public security, an intelligent video surveillance system that can analyze large-scale crowd scenes has become an urgent need. In this paper, we propose a system that integrates multiple crowd properties, including stationary and dynamic features, local and global characteristics, and historic statistics analysis in a unified framework. Specially our system consists of four modules. Crowd density module describes global density level and local density distribution with sparse spatial-temporal local binary pattern. Crowd segmentation module presents both global crowd grouping and local moving directions based on spatial-temporal dynamics. In crowd saliency module, salient regions are detected to alarm abnormal behaviors. At last, in order to analyze the historic features of video streaming, a historical statistics analysis module is introduced. Experiments on different crowd datasets show that our system is robust and feasible, and satisfies the requirements of video surveillance applications. © Springer Nature Singapore Pte Ltd. 2017.

关键词： Local binary pattern

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A robust homography estimation method based on keypoint consensus and appearance similarity

A robust homography estimation method based on keypoint cons...

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2012 13th IEEE International Conference on Multimedia and Expo, ICME 2012

作者： Yan, Qing Xu, Yi Yang, Xiaokang Institute of Image Communication and Information Processing Shanghai Key Lab. of Digital Media Processing and Transmition Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781467316590

In this paper, a robust homography estimation method is proposed to match multiview images in the uncalibrated case. This method formulates a new loss function to verify homography hypothesis, which combines models of key-point consensus and appearance similarity. In the consensus model, Lap lace distribution is exploited to better characterize the imprecision of key points. And in the appearance model, a truncated exponential function is utilized to represent the distribution of image similarity values. With these improvements, our method can be more robust in complex situations when a rather high percentage of key points are ambiguous and unreliable, and can output a more accurate homography that satisfies most pixels' geometric relationship. The experimenttal results highlight the robustness and accuracy of our method in the matching tasks of both synthetic images and real life photos. © 2012 IEEE.

关键词： Exponential functions

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Second-Order Controllability of Multi-Agent Systems with Multiple Leaders

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communications in Theoretical Physics 2016年第5期65卷 585-592页

作者：刘波史运涛苏厚胜韩潇 College of Science North China University of Technology Key Laboratory of Beijing for Field-Bus Technology & Automation North China University of Technology School of Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry of ChinaHuazhong University of Science and Technology

This paper proposes a new second-order continuous-time multi-agent model and analyzes the controllability of second-order multi-agent system with multiple leaders based on the asymmetric *** paper considers the more general case:velocity coupling topology is different from location coupling *** sufficient and necessary conditions are presented for the controllability of the system with multiple *** addition,the paper studies the controllability of the system with velocity damping *** results are given to illustrate the correctness of theoretical results.

关键词： controllability second-order multi-agent systems multiple leaders asymmetric topology

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Semantic segmentation network with local multi-scale attention for locating traffic sign 12

Semantic segmentation network with local multi-scale attenti...

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12th International Conference on Intelligent Computation Technology and Automation, ICICTA 2019

作者： Zhong, Shun Zheng, Zhuoyuan Yang, Peipei Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology Guilin541004 China

ISBN: (纸本)9781728142845

Semantic segmentation network is able to detect multi-scale traffic sign effectively. However, probabilities that different scale features participate in decision are equal in the network. In this work, we propose a local multi-scale attention module based on channel-attention, which extracts local features generated by dilated convolution and weights scale features. We demonstrate that adopting local multi-scale attention module on a semantic segmentation network achieves a better performance for locating multi-scale traffic signs than state-of-art convolutional networks by the experimental results on a Chinese traffic sign dataset. © 2019 IEEE.

关键词： Semantic Segmentation

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Gland segmentation based on morphological clues and feature fusion 2

Gland segmentation based on morphological clues and feature ...

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2nd International Conference on image processing, Computer Vision and Machine Learning, ICICML 2023

作者： Zeng, Lingqi Wang, Huadeng Guan, Junlin Guilin University of Electronic Technology Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin541004 China

ISBN: (纸本)9798350331417

The task of gland segmentation based on deep learning serves as a crucial auxiliary tool for diagnosing cancer. However, existing methods still exhibit shortcomings in handling gland adhesion and scale adaptability. To address these issues, we propose a gland segmentation approach that leverages morphological cues and multi-level feature fusion. By analyzing the morphological and imaging characteristics of glands, we have devised a novel scheme for label generation and loss weighting to guide model training. This scheme helps alleviate the challenge posed by the presence of adjacent glands and their adhesion. Additionally, by exploring the correlation between semantic features at different levels, we have developed a new feature fusion mechanism to mitigate issues related to model inaccuracies arising from variations in gland scales. Through experimental comparisons and discussions with classical and state-of-the-art methods, we demonstrate the effectiveness of our proposed approach. © 2023 IEEE.

关键词： Feature fusion Gland segmentation Morphological cues Multi-level feature

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Center matching scheme for K-means cluster ensembles

Center matching scheme for K-means cluster ensembles

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

作者： Zhang, Li Zhou, Weida Wu, Caili Huo, Jieting Zou, Haishuang Jiao, Licheng Institute of Intelligent Information Processing Key Laboratory of Intelligent Perception and Image Understanding Xidian University 710071 China

ISBN: (纸本)9780819478078

In this paper, a center matching scheme is proposed for constructing a consensus function in the k-means cluster ensemble learning. Each k-means clusterer outputs a sequence with k cluster centers. We randomly select a cluster center sequence as a reference one, and then we rearrange the other cluster center sequences according to the reference sequence. Then we label the data using these matched cluster center sequences. Hence we get multiple partitions or clusterings. Finally, multiple clusterings are combined to the best labeling by using combination rules, such as the majority voting rule, the weighted voting rule and the selective weighted voting rule. Experimental results on 7 UCI data sets show that our ensemble methods could improve the clustering results effectively. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Clustering algorithms

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Layer-aware forward error correction for mobile broadcast of layered media

Layer-aware forward error correction for mobile broadcast of...

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作者： Hellge, Cornelius Gómez-Barquero, David Schierl, Thomas Wiegand, Thomas Multimedia Communications Group Image Processing Department Fraunhofer HHI 10587 Berlin Germany Image Communication Laboratory Berlin Institute of Technology 10623 Berlin Germany Universidad Politécnica de Valencia 46022 Valencia Spain Image Processing Department Fraunhofer HHI 10587 Berlin Germany

The bitstream structure of layered media formats such as scalable video coding (SVC) or multiview video coding (MVC) opens up new opportunities for their distribution in Mobile TV services. Features like graceful degradation or the support of the 3-D experience in a backwards-compatible way are enabled. The reason is that parts of the media stream are more important than others with each part itself providing a useful media representation. Typically, the decoding of some parts of the bitstream is only possible, if the corresponding more important parts are correctly received. Hence, unequal error protection (UEP) can be applied protecting important parts of the bitstream more strongly than others. Mobile broadcast systems typically apply forward error correction (FEC) on upper layers to cope with transmission errors, which the physical layer FEC cannot correct. Today's FEC solutions are optimized to transmit single layer video. The exploitation of the dependencies in layered media codecs for UEP using FEC is the subject of this paper. The presented scheme, which is called layer-aware FEC (LA-FEC), incorporates the dependencies of the layered video codec into the FEC code construction. A combinatorial analysis is derived to show the potential theoretical gain in terms of FEC decoding probability and video quality. Furthermore, the implementation of LA-FEC as an extension of the Raptor FEC and the related signaling are described. The performance of layer-aware Raptor code with SVC is shown by experimental results in a DVB-H environment showing significant improvements achieved by LA-FEC. © 2011 IEEE.

关键词： Scalable video coding

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A Novel Method to Get Super-Resolution images from Low-Resolution Compressed Video

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The Journal of China Universities of Posts and Telecommunications 2005年第2期12卷 50-54页

作者： ZHOU Liang ZHU Xiu-chang Information Industry Ministry and Jiangsu Province Key Lab of Image Processing and Image Communication Nanjing University of Posts and Communications Nanjing 210003 P. R. China

In order to resolve the problems of discontented restoration effect and confined applying scope which exist in the current compressed video restoration algorithms, a novel method to get super-resolution images from low-resolution compressed video is proposed in this paper. At first, a uniform model is presented and the restoration problem in the Bayesian framework is formulated under the MAP criterion, then the focus is put on the hybrid motion-compensation and transform coding schemes, at last the methods of getting the parameters are provided. The results of the simulation clearly demonstrate that our method not only has the properties of finer vision effect and wider applying scope, but also performs better than those of current classical algorithms in the aspects of Peak Signal Noise Ratio （PSNR） under the basis of the same condition.

关键词： super-resolutlon compressed video restoration

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Joint Generic Learning and Multi-source Domain Adaptation on Unsupervised Face Recognition 1

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6th International Conference on Artificial Intelligence and Security,ICAIS 2020

作者： Xu, Zhi Han, Han Ji, Jianqiu Qiang, Baohua Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology Guilin541004 China

ISBN: (数字)9789811580833

ISBN: (纸本)9789811580826

For most machine learning algorithms, the performance of model trained on the source domain degenerates obviously when it is applied to the target domain because the distributions of both domains are different. Besides, in many cases, there is a lack of adequate supervised target domain training samples. In order to solve the mismatch between the domains and the lack of training samples, this paper proposes jointing domain adaptation and generic learning on solving unsupervised face recognition. Firstly, samples are selected randomly from multiple source and target domains which do not contain interest subjects and construct multiple sub-datasets. Secondly, learning a common subspace for each sub-dataset. In the common subspace, source and target domains can mutual interlace and their structures are well preserved, and we can get more discrimination information from multiple feature subspaces. Finally, the recognition is obtained by using combine strategies. The experimental results show that the recognition performance of the framework is better than that of the competitive ones. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Face recognition

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