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Deep Reinforcement Learning With Visual Attention for Vehicle Classification

文献类型：期刊论文

作者Zhao, Dongbin1,2; Chen, Yaran1; Lv, Le1
刊名IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS
出版日期2017-12-01
卷号9期号:4页码:356-367
关键词Convolutional Neural Network (Cnn) Reinforcement Learning Vehicle Classification Visual Attention
DOI10.1109/TCDS.2016.2614675
文献子类Article
英文摘要Automatic vehicle classification is crucial to intelligent transportation system, especially for vehicle-tracking by police. Due to the complex lighting and image capture conditions, image-based vehicle classification in real-world environments is still a challenging task and the performance is far from being satisfactory. However, owing to the mechanism of visual attention, the human vision system shows remarkable capability compared with the computer vision system, especially in distinguishing nuances processing. Inspired by this mechanism, we propose a convolutional neural network (CNN) model of visual attention for image classification. A visual attention-based image processing module is used to highlight one part of an image and weaken the others, generating a focused image. Then the focused image is input into the CNN to be classified. According to the classification probability distribution, we compute the information entropy to guide a reinforcement learning agent to achieve a better policy for image classification to select the key parts of an image. Systematic experiments on a surveillance-nature dataset which contains images captured by surveillance cameras in the front view, demonstrate that the proposed model is more competitive than the large-scale CNN in vehicle classification tasks.
WOS关键词OBJECT RECOGNITION ; FEATURES ; REPRESENTATION ; REGRESSION ; SALIENCY ; ROBOTS ; SCENES
WOS研究方向Computer Science ; Robotics ; Neurosciences & Neurology
语种英语
WOS记录号WOS:000418069600006
资助机构National Natural Science Foundation of China(61273136 ; National Key Research and Development Plan(2016YFB0101000) ; 61573353 ; 61533017)
源URL[http://ir.ia.ac.cn/handle/173211/14474]  
专题复杂系统管理与控制国家重点实验室_深度强化学习
作者单位1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式
GB/T 7714		 Zhao, Dongbin,Chen, Yaran,Lv, Le. Deep Reinforcement Learning With Visual Attention for Vehicle Classification[J]. IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS,2017,9(4):356-367.
APA Zhao, Dongbin,Chen, Yaran,&Lv, Le.(2017).Deep Reinforcement Learning With Visual Attention for Vehicle Classification.IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS,9(4),356-367.
MLA Zhao, Dongbin,et al."Deep Reinforcement Learning With Visual Attention for Vehicle Classification".IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS 9.4(2017):356-367.

入库方式： OAI收割

来源：自动化研究所

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