{"id":"https://openalex.org/W2524771588","doi":"https://doi.org/10.1109/tcds.2016.2614675","title":"Deep Reinforcement Learning With Visual Attention for Vehicle Classification","display_name":"Deep Reinforcement Learning With Visual Attention for Vehicle Classification","publication_year":2016,"publication_date":"2016-09-30","ids":{"openalex":"https://openalex.org/W2524771588","doi":"https://doi.org/10.1109/tcds.2016.2614675","mag":"2524771588"},"language":"en","primary_location":{"id":"doi:10.1109/tcds.2016.2614675","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcds.2016.2614675","pdf_url":null,"source":{"id":"https://openalex.org/S2488537894","display_name":"IEEE Transactions on Cognitive and Developmental Systems","issn_l":"2379-8920","issn":["2379-8920","2379-8939"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Cognitive and Developmental Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100624298","display_name":"Dongbin Zhao","orcid":"https://orcid.org/0000-0001-8218-9633"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongbin Zhao","raw_affiliation_strings":["State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China","University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8218-9633","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210094879"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053853035","display_name":"Yaran Chen","orcid":"https://orcid.org/0000-0001-9356-0610"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaran Chen","raw_affiliation_strings":["State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China","[State Key Laboratory of Management and Control for Complex Systems Institute of Automation, Chinese Academy of Sciences, Beijing, China]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210094879"]},{"raw_affiliation_string":"[State Key Laboratory of Management and Control for Complex Systems Institute of Automation, Chinese Academy of Sciences, Beijing, China]","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210094879"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100931698","display_name":"Le Lv","orcid":"https://orcid.org/0009-0000-9571-5049"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Le Lv","raw_affiliation_strings":["State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China","[State Key Laboratory of Management and Control for Complex Systems Institute of Automation, Chinese Academy of Sciences, Beijing, China]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210094879"]},{"raw_affiliation_string":"[State Key Laboratory of Management and Control for Complex Systems Institute of Automation, Chinese Academy of Sciences, Beijing, China]","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210094879"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":11.7956,"has_fulltext":false,"cited_by_count":205,"citation_normalized_percentile":{"value":0.98961247,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"9","issue":"4","first_page":"356","last_page":"367"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8744097352027893},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7252185940742493},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7111404538154602},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.6390990614891052},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5636022090911865},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.503764808177948},{"id":"https://openalex.org/keywords/eye-tracking","display_name":"Eye tracking","score":0.49898362159729004},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4615632891654968},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44954556226730347},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4369364380836487},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4193485975265503},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4131917953491211},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.37074029445648193}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8744097352027893},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7252185940742493},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7111404538154602},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.6390990614891052},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5636022090911865},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.503764808177948},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.49898362159729004},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4615632891654968},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44954556226730347},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4369364380836487},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4193485975265503},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4131917953491211},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.37074029445648193},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcds.2016.2614675","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcds.2016.2614675","pdf_url":null,"source":{"id":"https://openalex.org/S2488537894","display_name":"IEEE Transactions on Cognitive and Developmental Systems","issn_l":"2379-8920","issn":["2379-8920","2379-8939"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Cognitive and Developmental Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.44999998807907104}],"awards":[{"id":"https://openalex.org/G1731450854","display_name":null,"funder_award_id":"61273136","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5745859652","display_name":null,"funder_award_id":"61573353","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7163010157","display_name":"\u57fa\u4e8e\u6570\u636e\u7684\u5efa\u7b51\u7fa4\u53ca\u5206\u5e03\u5f0f\u80fd\u6e90\u7cfb\u7edf\u4e00\u4f53\u5316\u5efa\u6a21\u4e0e\u81ea\u5b66\u4e60\u4f18\u5316\u63a7\u5236","funder_award_id":"61533017","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W273955616","https://openalex.org/W1514535095","https://openalex.org/W1686810756","https://openalex.org/W1846479601","https://openalex.org/W1849277567","https://openalex.org/W1928906481","https://openalex.org/W1964858027","https://openalex.org/W1977728845","https://openalex.org/W1998808035","https://openalex.org/W2022508996","https://openalex.org/W2031686471","https://openalex.org/W2042230250","https://openalex.org/W2048299340","https://openalex.org/W2054279472","https://openalex.org/W2061879449","https://openalex.org/W2062118960","https://openalex.org/W2081106288","https://openalex.org/W2088698223","https://openalex.org/W2088767040","https://openalex.org/W2097041579","https://openalex.org/W2101786389","https://openalex.org/W2103748492","https://openalex.org/W2112796928","https://openalex.org/W2117539524","https://openalex.org/W2121863487","https://openalex.org/W2122710056","https://openalex.org/W2125896664","https://openalex.org/W2128272608","https://openalex.org/W2134557905","https://openalex.org/W2145287260","https://openalex.org/W2145339207","https://openalex.org/W2147527908","https://openalex.org/W2147800946","https://openalex.org/W2149095485","https://openalex.org/W2151103935","https://openalex.org/W2156652258","https://openalex.org/W2161969291","https://openalex.org/W2163605009","https://openalex.org/W2166049352","https://openalex.org/W2194775991","https://openalex.org/W2246099321","https://openalex.org/W2951527505","https://openalex.org/W2963542991","https://openalex.org/W4214717370","https://openalex.org/W4239661124","https://openalex.org/W6610017368","https://openalex.org/W6629368666","https://openalex.org/W6630875275","https://openalex.org/W6637373629","https://openalex.org/W6638641841","https://openalex.org/W6640376812","https://openalex.org/W6682137061","https://openalex.org/W6684191040","https://openalex.org/W6687483927"],"related_works":["https://openalex.org/W4306904969","https://openalex.org/W2911497689","https://openalex.org/W2952813363","https://openalex.org/W4360783045","https://openalex.org/W2963346891","https://openalex.org/W3176438653","https://openalex.org/W2770149305","https://openalex.org/W3167930666","https://openalex.org/W3014952856","https://openalex.org/W3010730661"],"abstract_inverted_index":{"Automatic":[0],"vehicle":[1,24,184],"classification":[2,25,124,145,185],"is":[3,29,37,92,113,176],"crucial":[4],"to":[5,15,44,94,118,122,132,138,146],"intelligent":[6],"transportation":[7],"system,":[8,62],"especially":[9,63],"for":[10,83,143],"vehicle-tracking":[11],"by":[12,69,164],"police.":[13],"Due":[14],"the":[16,35,45,50,59,103,110,116,123,129,148,168,173,180],"complex":[17],"lighting":[18],"and":[19,34,101],"image":[20,84,89,100,112,144],"capture":[21],"conditions,":[22],"image-based":[23],"in":[26,64,167,183],"real-world":[27],"environments":[28],"still":[30],"a":[31,74,106,134,140,157],"challenging":[32],"task":[33],"performance":[36],"far":[38],"from":[39],"being":[40],"satisfactory.":[41],"However,":[42],"owing":[43],"mechanism":[46],"of":[47,80,98,151],"visual":[48,81,87],"attention,":[49],"human":[51],"vision":[52,61],"system":[53],"shows":[54],"remarkable":[55],"capability":[56],"compared":[57],"with":[58],"computer":[60],"distinguishing":[65],"nuances":[66],"processing.":[67],"Inspired":[68],"this":[70],"mechanism,":[71],"we":[72,127],"propose":[73],"convolutional":[75],"neural":[76],"network":[77],"(CNN)":[78],"model":[79,175],"attention":[82],"classification.":[85],"A":[86],"attention-based":[88],"processing":[90],"module":[91],"used":[93],"highlight":[95],"one":[96],"part":[97],"an":[99,152],"weaken":[102],"others,":[104],"generating":[105],"focused":[107,111],"image.":[108,153],"Then":[109],"input":[114],"into":[115],"CNN":[117,182],"be":[119],"classified.":[120],"According":[121],"probability":[125],"distribution,":[126],"compute":[128],"information":[130],"entropy":[131],"guide":[133],"reinforcement":[135],"learning":[136],"agent":[137],"achieve":[139],"better":[141],"policy":[142],"select":[147],"key":[149],"parts":[150],"Systematic":[154],"experiments":[155],"on":[156],"surveillance-nature":[158],"dataset":[159],"which":[160],"contains":[161],"images":[162],"captured":[163],"surveillance":[165],"cameras":[166],"front":[169],"view,":[170],"demonstrate":[171],"that":[172],"proposed":[174],"more":[177],"competitive":[178],"than":[179],"large-scale":[181],"tasks.":[186]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":21},{"year":2023,"cited_by_count":29},{"year":2022,"cited_by_count":20},{"year":2021,"cited_by_count":30},{"year":2020,"cited_by_count":31},{"year":2019,"cited_by_count":31},{"year":2018,"cited_by_count":17},{"year":2017,"cited_by_count":8}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
