CASIA OpenIR  > 复杂系统管理与控制国家重点实验室  > 深度强化学习
Deep Reinforcement Learning With Visual Attention for Vehicle Classification
Zhao, Dongbin1,2; Chen, Yaran1; Lv, Le1
Source PublicationIEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS
2017-12-01
Volume9Issue:4Pages:356-367
SubtypeArticle
AbstractAutomatic 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.
KeywordConvolutional Neural Network (Cnn) Reinforcement Learning Vehicle Classification Visual Attention
WOS HeadingsScience & Technology ; Technology ; Life Sciences & Biomedicine
DOI10.1109/TCDS.2016.2614675
WOS KeywordOBJECT RECOGNITION ; FEATURES ; REPRESENTATION ; REGRESSION ; SALIENCY ; ROBOTS ; SCENES
Indexed BySCI ; SSCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(61273136 ; National Key Research and Development Plan(2016YFB0101000) ; 61573353 ; 61533017)
WOS Research AreaComputer Science ; Robotics ; Neurosciences & Neurology
WOS SubjectComputer Science, Artificial Intelligence ; Robotics ; Neurosciences
WOS IDWOS:000418069600006
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Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/14474
Collection复杂系统管理与控制国家重点实验室_深度强化学习
Affiliation1.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
Recommended Citation
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.
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