{"id":"https://openalex.org/W4396214338","doi":"https://doi.org/10.1109/tits.2024.3390576","title":"A Coarse-to-Fine Deep Learning Based Framework for Traffic Light Recognition","display_name":"A Coarse-to-Fine Deep Learning Based Framework for Traffic Light Recognition","publication_year":2024,"publication_date":"2024-04-29","ids":{"openalex":"https://openalex.org/W4396214338","doi":"https://doi.org/10.1109/tits.2024.3390576"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2024.3390576","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2024.3390576","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Intelligent Transportation 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/A5090228481","display_name":"Zikai Yao","orcid":"https://orcid.org/0000-0003-1327-2366"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]},{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["CN","SG"],"is_corresponding":true,"raw_author_name":"Zikai Yao","raw_affiliation_strings":["School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen, China","School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen, China","institution_ids":["https://openalex.org/I157773358"]},{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107858135","display_name":"Qiang Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Liu","raw_affiliation_strings":["School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen, China","Guangdong Marshell Electric Technology Company, Zhaoqing, China"],"affiliations":[{"raw_affiliation_string":"School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen, China","institution_ids":["https://openalex.org/I157773358"]},{"raw_affiliation_string":"Guangdong Marshell Electric Technology Company, Zhaoqing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101541695","display_name":"Jie Fu","orcid":"https://orcid.org/0000-0002-2593-995X"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Fu","raw_affiliation_strings":["School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101712963","display_name":"Qian Xie","orcid":"https://orcid.org/0000-0002-8290-2483"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qian Xie","raw_affiliation_strings":["School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100374360","display_name":"Bo Li","orcid":"https://orcid.org/0000-0001-6709-0942"},"institutions":[{"id":"https://openalex.org/I4210113138","display_name":"Guangzhou Automobile Group (China)","ror":"https://ror.org/026fzn952","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210113138"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Li","raw_affiliation_strings":["Research and Development Center, Guangzhou Automobile Group Company Ltd., Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Research and Development Center, Guangzhou Automobile Group Company Ltd., Guangzhou, China","institution_ids":["https://openalex.org/I4210113138"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100347581","display_name":"Qing Ye","orcid":"https://orcid.org/0000-0003-3956-3348"},"institutions":[{"id":"https://openalex.org/I4210107248","display_name":"Merchants Chongqing Communications Research and Design Institute","ror":"https://ror.org/01jvv7h21","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210107248"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qing Ye","raw_affiliation_strings":["Research and Development Center, China Merchants Chongqing Communications Technology Research and Design Institute Company Ltd., Chongqing, China"],"affiliations":[{"raw_affiliation_string":"Research and Development Center, China Merchants Chongqing Communications Technology Research and Design Institute Company Ltd., Chongqing, China","institution_ids":["https://openalex.org/I4210107248"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100404130","display_name":"Qing Li","orcid":"https://orcid.org/0000-0002-7930-2145"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Qing Li","raw_affiliation_strings":["School of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"School of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I129604602"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5090228481"],"corresponding_institution_ids":["https://openalex.org/I157773358","https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":3.6632,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.9411499,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"25","issue":"10","first_page":"13887","last_page":"13899"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9950000047683716,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9950000047683716,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9925000071525574,"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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.991100013256073,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6311572790145874},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6289466023445129},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6098924875259399},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5975847244262695},{"id":"https://openalex.org/keywords/traffic-signal","display_name":"Traffic signal","score":0.54322749376297},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.510793924331665},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4902198910713196},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45439034700393677},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.43950536847114563},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41550207138061523},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38059931993484497},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3484035134315491},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.13697528839111328}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6311572790145874},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6289466023445129},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6098924875259399},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5975847244262695},{"id":"https://openalex.org/C2987419075","wikidata":"https://www.wikidata.org/wiki/Q8004","display_name":"Traffic signal","level":2,"score":0.54322749376297},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.510793924331665},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4902198910713196},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45439034700393677},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.43950536847114563},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41550207138061523},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38059931993484497},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3484035134315491},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.13697528839111328},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2024.3390576","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2024.3390576","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5283183765","display_name":null,"funder_award_id":"2022A1515010692","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"}],"funders":[{"id":"https://openalex.org/F4320337111","display_name":"Basic and Applied Basic Research Foundation of Guangdong Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1559773506","https://openalex.org/W1562810981","https://openalex.org/W1861492603","https://openalex.org/W1985791174","https://openalex.org/W2194775991","https://openalex.org/W2222317246","https://openalex.org/W2304191769","https://openalex.org/W2534186952","https://openalex.org/W2615277952","https://openalex.org/W2616247523","https://openalex.org/W2762219805","https://openalex.org/W2883223908","https://openalex.org/W2903632709","https://openalex.org/W2925287836","https://openalex.org/W2942771274","https://openalex.org/W2963037989","https://openalex.org/W2963163009","https://openalex.org/W2963315052","https://openalex.org/W2963857746","https://openalex.org/W2982083293","https://openalex.org/W2990763144","https://openalex.org/W3004591935","https://openalex.org/W3041622297","https://openalex.org/W3041970172","https://openalex.org/W3047375952","https://openalex.org/W3084946993","https://openalex.org/W3092663126","https://openalex.org/W3102564565","https://openalex.org/W3123061922","https://openalex.org/W3126502934","https://openalex.org/W3135688577","https://openalex.org/W3156861611","https://openalex.org/W3196007291","https://openalex.org/W4210667216","https://openalex.org/W4280492519","https://openalex.org/W4282919254","https://openalex.org/W4285813030","https://openalex.org/W4313241614","https://openalex.org/W4313555467","https://openalex.org/W4320040537","https://openalex.org/W4367146890","https://openalex.org/W4372263412","https://openalex.org/W4386076325","https://openalex.org/W4386319838"],"related_works":["https://openalex.org/W3135697610","https://openalex.org/W4375867731","https://openalex.org/W2359800014","https://openalex.org/W2085033728","https://openalex.org/W4285411112","https://openalex.org/W2171299904","https://openalex.org/W1647606319","https://openalex.org/W2922442631","https://openalex.org/W4298130764","https://openalex.org/W4390494008"],"abstract_inverted_index":{"Accurate":[0],"recognition":[1,164],"of":[2,19,33,69,92,109,136,166,178,196,213,218,223,236],"traffic":[3,12,20,34,49,63,110,137,168,189,244],"light":[4,21,50,64,138,190,245],"plays":[5],"a":[6,76,97,144,211,216,221],"crucial":[7],"role":[8],"in":[9,83],"ensuring":[10],"road":[11],"safety.":[13],"Due":[14],"to":[15],"the":[16,24,89,103,115,128,133,176,206,230,233],"wide":[17],"variety":[18],"classes":[22,108],"and":[23,30,75,131,152,215,239],"inherent":[25],"conflict":[26],"between":[27],"location":[28],"determination":[29],"intra-class":[31],"classification":[32],"lights,":[35],"existing":[36],"deep":[37],"learning-based":[38],"methods":[39],"cannot":[40],"obtain":[41],"satisfactory":[42],"results,":[43],"making":[44],"them":[45],"still":[46],"unreliable":[47],"as":[48],"recognizers.":[51],"To":[52,174],"address":[53],"this":[54],"issue,":[55],"we":[56,87,113,142,181],"propose":[57,143],"an":[58,70,121,193],"effective":[59],"Coarse-to-fine":[60],"framework":[61],"for":[62,155,171,243],"recognition,":[65],"which":[66,125],"is":[67],"consisted":[68],"enhanced":[71],"super":[72,93,116,139,156],"class":[73,94,117,157],"detector":[74,118],"fine-grained":[77,145],"classifier.":[78],"The":[79],"main":[80],"contributions":[81],"lie":[82],"three":[84],"aspects.":[85],"Firstly,":[86],"determine":[88],"optimal":[90],"number":[91],"by":[95,106,119],"adopting":[96],"clustering":[98],"algorithm.":[99],"It":[100,160],"can":[101,161,209],"alleviate":[102],"effect":[104],"caused":[105],"similar":[107,172],"light.":[111],"Secondly,":[112],"enhance":[114],"introducing":[120],"additional":[122],"prediction":[123],"layer,":[124],"enable":[126],"utilizing":[127],"shadow":[129],"features":[130],"improving":[132],"detection":[134],"performance":[135,165],"class.":[140],"Lastly,":[141],"classifier":[146],"based":[147],"on":[148,184],"depth-wise":[149],"separable":[150],"convolution":[151],"expansion":[153],"layer":[154],"candidate":[158],"classification.":[159],"achieve":[162,210],"superior":[163],"different":[167],"lights":[169],"especially":[170],"classes.":[173],"evaluate":[175],"effectiveness":[177,242],"our":[179,237],"method,":[180],"conduct":[182],"experiments":[183],"WPI":[185],"(Worcester":[186],"Polytechnic":[187],"Institute)":[188],"dataset.":[191],"With":[192],"input":[194],"size":[195],"416":[197,204],"<inline-formula":[198],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[199],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">":[200],"<tex-math":[201],"notation=\"LaTeX\">${\\times}$</tex-math>":[202],"</inline-formula>":[203],"pixels,":[205],"proposed":[207],"method":[208,238],"precision":[212],"99.04%":[214],"recall":[217],"97.40%":[219],"with":[220,226],"speed":[222],"9.9ms.":[224],"Compared":[225],"other":[227],"state-of-the-art":[228],"methods,":[229],"results":[231],"demonstrate":[232],"significant":[234],"competitiveness":[235],"its":[240],"high":[241],"recognition.":[246]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":3}],"updated_date":"2026-04-11T08:14:18.477133","created_date":"2025-10-10T00:00:00"}
