{"id":"https://openalex.org/W4200223240","doi":"https://doi.org/10.1145/3490725.3490728","title":"Fast Traffic Light Recognition Using a Lightweight Attention-Enhanced Model","display_name":"Fast Traffic Light Recognition Using a Lightweight Attention-Enhanced Model","publication_year":2021,"publication_date":"2021-09-17","ids":{"openalex":"https://openalex.org/W4200223240","doi":"https://doi.org/10.1145/3490725.3490728"},"language":"en","primary_location":{"id":"doi:10.1145/3490725.3490728","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3490725.3490728","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 The 4th International Conference on Machine Learning and Machine Intelligence","raw_type":"proceedings-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/A5019766178","display_name":"Xu Chen","orcid":"https://orcid.org/0000-0002-7073-147X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Chen","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091503481","display_name":"Changwei Luo","orcid":"https://orcid.org/0000-0002-3107-7022"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changwei Luo","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.097,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.42850232,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"15","last_page":"20"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994999766349792,"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":0.9994999766349792,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental 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":0.9975000023841858,"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":0.8222916126251221},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6754640340805054},{"id":"https://openalex.org/keywords/traffic-signal","display_name":"Traffic signal","score":0.5604974627494812},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.49546849727630615},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4836791455745697},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.40675127506256104},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38148462772369385},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3549617528915405}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8222916126251221},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6754640340805054},{"id":"https://openalex.org/C2987419075","wikidata":"https://www.wikidata.org/wiki/Q8004","display_name":"Traffic signal","level":2,"score":0.5604974627494812},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.49546849727630615},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4836791455745697},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.40675127506256104},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38148462772369385},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3549617528915405},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3490725.3490728","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3490725.3490728","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 The 4th International Conference on Machine Learning and Machine Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6700000166893005,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1985791174","https://openalex.org/W2161969291","https://openalex.org/W2291942460","https://openalex.org/W2460736120","https://openalex.org/W2615277952","https://openalex.org/W2762219805","https://openalex.org/W4249989836","https://openalex.org/W4285718182"],"related_works":["https://openalex.org/W1504288058","https://openalex.org/W2331674254","https://openalex.org/W2811390910","https://openalex.org/W2167293474","https://openalex.org/W2146076056","https://openalex.org/W3042897387","https://openalex.org/W2546942002","https://openalex.org/W2534909612","https://openalex.org/W2016461833","https://openalex.org/W3197541072"],"abstract_inverted_index":{"Traffic":[0],"light":[1,32],"recognition":[2],"is":[3,65,76,125],"a":[4,61,71],"research":[5],"hotspot":[6],"in":[7,17,35,58,67],"the":[8,18,21,24,28,36,42,48,80,88,107,128,134,139,154,170],"field":[9],"of":[10,23,30,47,51,84,111,119,130,172],"intelligent":[11],"transportation":[12],"and":[13,96],"unmanned":[14],"driving.":[15],"However,":[16],"actual":[19,43],"scene,":[20],"complexity":[22],"surrounding":[25],"environment":[26],"increases":[27],"difficulty":[29],"traffic":[31,52,59,145,157,173],"detection,":[33],"resulting":[34],"detection":[37],"accuracy":[38,171],"often":[39],"cannot":[40],"meet":[41],"requirements.":[44],"In":[45],"view":[46],"small":[49,131],"scale":[50],"lights":[53],"compared":[54],"with":[55],"other":[56],"targets":[57],"scenes,":[60],"lightweight":[62],"attention-enhanced":[63,72],"model":[64],"proposed":[66,77,89,165],"this":[68],"paper.":[69],"Firstly,":[70],"feature":[73,81,113],"extraction":[74],"network":[75,90,140],"to":[78,106,127],"increase":[79],"description":[82],"ability":[83],"small-scale":[85],"objects;":[86,132],"Secondly,":[87],"structure":[91],"integrates":[92],"high-level":[93,120],"semantic":[94,121],"features":[95],"low-level":[97,112],"detail":[98],"features,":[99,123],"which":[100,124],"not":[101],"only":[102],"gives":[103],"full":[104],"play":[105],"strong":[108],"information":[109,122],"representation":[110],"details,":[114],"but":[115],"also":[116],"makes":[117,138],"use":[118],"conducive":[126],"classification":[129],"Thirdly,":[133],"refinement":[135],"anchor":[136],"strategy":[137],"more":[141],"suitable":[142],"for":[143],"detecting":[144],"lights.":[146],"We":[147],"have":[148],"carried":[149],"out":[150],"experimental":[151],"verification":[152],"on":[153],"open":[155],"Bosch":[156],"signal":[158,174],"dataset.":[159],"Experimental":[160],"results":[161],"show":[162],"that":[163],"our":[164],"algorithm":[166],"can":[167],"dramatically":[168],"improve":[169],"recognition.":[175]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}