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26th European Conference on Artificial Intelligence, ECAI 2023

作者： Chen, Yirui Wei, Pengjin Liu, Zhenhuan Wang, Bingchao Yang, Jie Liu, Wei Institute of Image Processing and Pattern Recognition Department of Automation Shanghai Jiao Tong University China Key Laboratory of System Control and Information Processing Ministry of Education China

ISBN: (纸本)9781643684369

Producing traversability maps and understanding the surroundings are crucial prerequisites for autonomous navigation. In this paper, we address the problem of traversability assessment using point clouds. We propose a novel pillar feature extraction module that utilizes PointNet to capture features from point clouds organized in vertical volume and a 2D encoder-decoder structure to conduct traversability classification instead of the widely used 3D convolutions. This results in less computational cost while even better performance is achieved at the same time. We then propose a new spatio-temporal attention module to fuse multi-frame information, which can properly handle the varying density problem of LIDAR point clouds, and this makes our module able to assess distant areas more accurately. Comprehensive experimental results on augmented Semantic KITTI and RELLIS-3D datasets show that our method is able to achieve superior performance over existing approaches both quantitatively and quantitatively. Our code is publicly available at https://***/chenyirui/FASTC. © 2023 The Authors.

关键词： Semantics

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Face Recognition with Convolutional Neural Networks and subspace learning 2

Face Recognition with Convolutional Neural Networks and subs...

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2nd International Conference on image, Vision and Computing, ICIVC 2017

作者： Wan, Lihong Liu, Na Huo, Hong Tao, Fang Institute of Image Processing and Pattern Recognition Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China

ISBN: (纸本)9781509062379

Deep learning is widely used in computer vision. In this study, we present a new method based on Convolutional Neural Networks (CNN) and subspace learning for face recognition under two circumstances. A very deep CNN architecture called VGG-Face, which learned on a large scale database, is used as feature extractor to extract the activation vector of the fully connected layer in the CNN architecture. Then, two types of subspace learning methods, namely, linear discriminate analysis (LDA) and whitening principal component analysis (WPCA), are respectively introduced to learn the subspace of the activation vectors for face recognition under multiple samples per subject and single sample per subject circumstances. The goals of applying subspace learning to the activation vectors are obtaining compact representation (dimensionality reduction) and performance improvement. Experiments on two face databases (CMU PIE and FERET) demonstrate the effectiveness of VGG-Face + LDA and VGG-Face + WPCA, compared with state-of-the-art methods. © 2017 IEEE.

关键词： Principal component analysis

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Two Novel Cellular Neural Networks Based on Mem-elements

Two Novel Cellular Neural Networks Based on Mem-elements

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第三十四届中国控制会议

作者： SHEN Yi JIA Zhen Zhen WANG Xiao Ping LIU Yang School of Automation Huazhong University of Science and Technology Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Research Institute of Huazhong University of Science and Technology in Shenzhen

ISBN: (纸本)9781467374439

Two types of novel cellular neural networks based on mem-elements are proposed, namely, MC-CNN and *** MC-CNN lets a memcapacitor replace the conventional linear capacitor of a cellular neural network cell. This improvement takes advantage of the nanoscale of memcapacitor and its natural nonlinearity, which makes the MC-CNN more compact and the output function simplified. Mathematical analysis of stability and simulation of image processing is presented to verify the feasibility and performance of MC-CNN. The EM-CNN is an economical improvement of the memristor synapse cellular neural network. In the EM-CNN, based on the symmetry of CNN templates, the amount of memristors and voltage-controlled current source is largely reduced. Thus, the EM-CNN is not only economical on the fabricating cost of CNN but also possesses a simpler cell structure which is beneficial to better implementation of CNN.

关键词： Cellular Neural Network,Memcapacitor,Memristor,image processing

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Four development stages of collective intelligence

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Frontiers of Information Technology & Electronic Engineering 2024年第7期25卷 903-916页

作者： Renbin XIAO School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China Key Laboratory of Image Information Processing and Intelligent Control Ministry of EducationWuhan 430074China

The new generation of artificial intelligence(AI)research initiated by Chinese scholars conforms to the needs of a new information environment changes,and strives to advance traditional artificial intelligence(AI 1.0)to a new stage of AI *** one of the important components of AI,collective intelligence(CI 1.0),i.e.,swarm intelligence,is developing to the stage of CI 2.0(crowd intelligence).Through in-depth analysis and informative argumentation,it is found that an incompatibility exists between CI 1.0 and CI ***,CI 1.5 is introduced to build a bridge between the above two stages,which is based on biocollaborative behavioral *** 1.5 is the transition from CI 1.0 to CI 2.0,which contributes to the compatibility of the two ***,a new interpretation of the meta-synthesis of wisdom proposed by Qian Xuesen is *** meta-synthesis of wisdom,as an improvement of crowd intelligence,is an advanced stage of bionic intelligence,i.e.,CI *** is pointed out that the dual-wheel drive of large language models and big data with deep uncertainty is an evolutionary path from CI 2.0 to CI 3.0,and some elaboration is *** a result,we propose four development stages(CI 1.0,CI 1.5,CI 2.0,and CI 3.0),which form a complete framework for the development of *** different stages are progressively improved and have good *** to the dominant role of cooperation in the development stages of CI,three types of cooperation in CI are discussed:indirect regulatory cooperation in lower organisms,direct communicative cooperation in higher organisms,and shared intention based collaboration in *** division is the main form of achieving cooperation and,for this reason,this paper investigates the relationship between the complexity of behavior and types of labor ***,based on the overall understanding of the four development stages of CI,the future development direction and research issues of CI are explored.

关键词： Collective intelligence Meta-synthesis of wisdom Incompatibility Labor division Cooperative behavior Collective intelligence emergence Large language model

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Three-dimensional double directional filter for tracking and detecting moving dim weak target

Three-dimensional double directional filter for tracking and...

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MIPPR 2005: image Analysis Techniques

作者： Li, Meng Zhang, Tianxu Yang, Weidong Mao, Haiceng State Education Commission Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

The aim of the present work is to assess the performance of three-dimensional Double Directional Filtering (TDDDF) algorithm for detecting and tracking a weak moving dim target against a complex cluttered background in infrared image sequences. This paper proposes an novel TDDDF to improve the integrated signal-to-clutter ratio (ISCR) and enhance the three-dimensional directional filter's (TDDF) target energy accumulation ability further. Since the TDDDF do well to whitening noise (or quasi whitening noise) but not so sensitive to complex cloudscene background, prior to the filtering, a newly pre-whitening method termed Spatial-Temporal Adaptive Filtering algorithm is used here to suppress clutter background. Extensive experiment results demonstrate the proposed algorithm's ability in detecting weak dim point target against cloud-cluttered background. Finally, performance comparisons of the proposed algorithm and TDDF, on real IR image data, are presented in which the advantages of the proposed TDDDF filters are shown.

关键词： Tracking (position)

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3D multipath planning for UAV based on network graph

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Journal of Systems Engineering and Electronics 2011年第4期22卷 640-646页

作者： Xin Liu Chengping Zhou Mingyue Ding Institute for Pattern Recognition and Artificial Intelligence Key Laboratory of National Defense Science and Technology forMulti-spectral Information Processing Technologies Huazhong University of Science and Technology Wuhan 430074 R R. China School of Life Science and Technology Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430072 P. R. China

According to the characteristic and the requirement of multipath planning, a new multipath planning method is proposed based on network. This method includes two steps： the construction of network and multipath searching. The construction of network proceeds in three phases： the skeleton extraction of the configuration space, the judgment of the cross points in the skeleton and how to link the cross points to form a network. Multipath searching makes use of the network and iterative penalty method （IPM） to plan multi-paths, and adjusts the planar paths to satisfy the requirement of maneuverability of unmanned aerial vehicle （UAV）. In addition, a new height planning method is proposed to deal with the height planning of 3D route. The proposed algorithm can find multiple paths automatically according to distribution of terrain and threat areas with high efficiency. The height planning can make 3D route following the terrain. The simulation experiment illustrates the feasibility of the proposed method.

关键词： path planning skeleton graph iterative penaltymethod （IPM） network graph.

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Dynamic modeling and simulation test of a 60 kW PEMFC generation system

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2011年第6期12卷 475-482页

作者： Ying-ying ZHANG Ji-chang SUN Ying ZHANG Xi LI Ouang-yi CAO Shandong Provincial Key Laboratory of Ocean Environment Monitoring Technology Shandong Academy of Sciences Institute of Oceanographic Instrumentation Qingdao 266001 China Control Science and Engineering Department Key Laboratory of Education Ministry for Image Processing and lntelligent Control Huazhong University of Science & Technology Wuhan 430074 China Fuel Cell Institute Department of Automation Shanghai Jiao Tong University Shanghai 200030 China

In this paper,a 60 kW proton exchange membrane fuel cell(PEMFC) generation system is modeled in order to design the system parameters and investigate the static and dynamic characteristics for control *** achieve an overall system model,the system is divided into five modules:the PEMFC stack(anode and cathode flows,membrane hydration,and stack voltage and power),cathode air supply(air compressor,supply manifold,cooler,and humidifier),anode fuel supply(hydrogen valve and humidifier),cathode exhaust exit(exit manifold and water return),and power conditioning(DC/DC and DC/AC) *** a combination of empirical and physical modeling techniques,the model is developed to set the operation conditions of current,temperature,and cathode and anode gas flows and pressures,which have major impacts on system *** current model is based on a 60 kW PEMFC power plant designed for residential applications and takes account of the electrochemical and thermal aspects of chemical reactions within the stack as well as flows of reactants across the *** simulation tests show that the system model can represent the static and dynamic characteristics of a 60 kW PEMFC generation system,which is mathematically simple for system parameters and control designs.

关键词： Proton exchange membrane fuel cell(PEMFC) Generation system Dynamic simulation model Reactant flow

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Semiglobal observer-based leader-following consensus with input saturation

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IEEE Transactions on Industrial Electronics 2014年第6期61卷 2842-2850页

作者： Su, Housheng Chen, Michael Z.Q. Wang, Xiaofan Lam, James Key Laboratory of Image Processing and Intelligent Control of the Ministry of Education of China School of Automation Huazhong University of Science and Technology Wuhan 430074 China Department of Mechanical Engineering University of Hong Kong Pokfulam Hong Kong Department of Automation Shanghai Jiao Tong University Shanghai 200240 China

This paper studies the observer-based leader-following consensus of a linear multiagent system on switching networks, in which the input of each agent is subject to saturation. Based on a low-gain output feedback method, distributed consensus protocols are developed. Under the assumptions that the networks are connected or jointly connected and that each agent is asymptotically null controllable with bounded controls and detectable, semiglobal observer-based leader-following consensus of the multiagent system can be reached on switching networks. A numerical example is presented to illustrate the theoretical results. © 1982-2012 IEEE.

关键词： Multi agent systems

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Fusion Algorithm for Remote Sensing images Based on Nonsubsampled Contourlet Transform

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自动化学报 2008年第3期34卷 274-281页

作者： YANG Xiao-Hui JIAO Li-Cheng Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information ProcessingXidian UniversityXi＇an 710071P.R.China

就图象的人的视觉系统和特征而言，新奇图象熔化策略为在 nonsubsampled contourlet 的高分辨率图象和 multispectral 图象转变的 panchro matic (NSCT ) 被介绍域。NSCT 能由它好 multiresolution，移动不变性，和高 directionality ... 详细信息

就图象的人的视觉系统和特征而言，新奇图象熔化策略为在 nonsubsampled contourlet 的高分辨率图象和 multispectral 图象转变的 panchro matic (NSCT ) 被介绍域。NSCT 能由它好 multiresolution，移动不变性，和高 directionality 的特征的优点在图象给 asymptotic 边和轮廓的最佳的表示。紧张部件增加策略基于 LHS 变换被介绍进 NSCT 领域保存空间分辨率和颜色内容。熔化方法建议了的实验表演能改进空间分辨率并且保留光谱信息同时，并且与传统的原则部件分析( PCA )相比在视觉效果和量的肛门 ysis 两个都有改进方法， intensity-hue-saturation (代表耶稣之符号)变换技术，小浪变换加权的熔化方法，相应小浪基于变换的熔化方法，和 contourlet 基于变换的熔化方法。

关键词：混合算法遥感图象强度组分添加非子采样Contourlet变换 LHS变换

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Robust Electric Vehicle Routing Problem with Time Windows under Demand Uncertainty and Weight-Related Energy Consumption

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Complex System Modeling and Simulation 2022年第1期2卷 18-34页

作者： Yindong Shen Leqin Yu Jingpeng Li Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China Division of Computer Science and Mathematics University of StirlingStirlingFK94LAUK

Vehicle routing problem with time windows(VRPTW)is a core combinatorial optimization problem in distribution *** electric vehicle routing problem with time windows under demand uncertainty and weight-related energy consumption is an extension of the *** some researchers have studied either the electric VRPTW with nonlinear energy consumption model or the impact of the uncertain customer demand on the conventional vehicles,the literature on the integration of uncertain demand and energy consumption of electric vehicles is still ***,practically,it is usually not feasible to ignore the uncertainty of customer demand and the weight-related energy consumption of electronic vehicles(EVs)in actual ***,we propose the robust optimization model based on a route-related uncertain set to tackle this ***,adaptive large neighbourhood search heuristic has been developed to solve the problem due to the NP-hard nature of the *** effectiveness of the method is verified by experiments,and the influence of uncertain demand and uncertain parameters on the solution is further explored.

关键词： electric vehicle routing problem time windows uncertain demand energy consumption model robust optimization adaptive large neighbourhood search

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