{"id":"https://openalex.org/W2739574231","doi":"https://doi.org/10.1109/ivs.2017.7995785","title":"An efficient vision-based traffic light detection and state recognition for autonomous vehicles","display_name":"An efficient vision-based traffic light detection and state recognition for autonomous vehicles","publication_year":2017,"publication_date":"2017-06-01","ids":{"openalex":"https://openalex.org/W2739574231","doi":"https://doi.org/10.1109/ivs.2017.7995785","mag":"2739574231"},"language":"en","primary_location":{"id":"doi:10.1109/ivs.2017.7995785","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2017.7995785","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Intelligent Vehicles Symposium (IV)","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/A5101535846","display_name":"Sanjay Saini","orcid":"https://orcid.org/0000-0001-9399-5788"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Sanjay Saini","raw_affiliation_strings":["SMR Automotive Systems India Limited, Bangalore, India"],"affiliations":[{"raw_affiliation_string":"SMR Automotive Systems India Limited, Bangalore, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109349559","display_name":"S. Nikhil","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"S Nikhil","raw_affiliation_strings":["SMR Automotive Systems India Limited, Bangalore, India"],"affiliations":[{"raw_affiliation_string":"SMR Automotive Systems India Limited, Bangalore, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000237783","display_name":"Krishna Reddy Konda","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Krishna Reddy Konda","raw_affiliation_strings":["SMR Automotive Systems India Limited, Bangalore, India"],"affiliations":[{"raw_affiliation_string":"SMR Automotive Systems India Limited, Bangalore, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110288179","display_name":"Harish S Bharadwaj","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Harish S Bharadwaj","raw_affiliation_strings":["SMR Automotive Systems India Limited, Bangalore, India"],"affiliations":[{"raw_affiliation_string":"SMR Automotive Systems India Limited, Bangalore, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034570061","display_name":"Nivethika Ganeshan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"N Ganeshan","raw_affiliation_strings":["SMR Automotive Systems India Limited, Bangalore, India"],"affiliations":[{"raw_affiliation_string":"SMR Automotive Systems India Limited, Bangalore, India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101535846"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.8728,"has_fulltext":false,"cited_by_count":77,"citation_normalized_percentile":{"value":0.94764955,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"606","last_page":"611"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9988999962806702,"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"}},"topics":[{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","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"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.998199999332428,"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/T12707","display_name":"Vehicle License Plate Recognition","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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":0.741481363773346},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6993616819381714},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6987581849098206},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6292872428894043},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6169439554214478},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.5808466672897339},{"id":"https://openalex.org/keywords/histogram-of-oriented-gradients","display_name":"Histogram of oriented gradients","score":0.48417264223098755},{"id":"https://openalex.org/keywords/traffic-signal","display_name":"Traffic signal","score":0.48108145594596863},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.46886545419692993},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4662935137748718},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4138646125793457},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.19726935029029846},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.11119499802589417}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.741481363773346},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6993616819381714},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6987581849098206},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6292872428894043},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6169439554214478},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.5808466672897339},{"id":"https://openalex.org/C17426736","wikidata":"https://www.wikidata.org/wiki/Q419918","display_name":"Histogram of oriented gradients","level":4,"score":0.48417264223098755},{"id":"https://openalex.org/C2987419075","wikidata":"https://www.wikidata.org/wiki/Q8004","display_name":"Traffic signal","level":2,"score":0.48108145594596863},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.46886545419692993},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4662935137748718},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4138646125793457},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.19726935029029846},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.11119499802589417}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ivs.2017.7995785","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2017.7995785","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.6499999761581421,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1562810981","https://openalex.org/W1968974896","https://openalex.org/W1970873657","https://openalex.org/W1981562962","https://openalex.org/W2001884204","https://openalex.org/W2021383150","https://openalex.org/W2056889172","https://openalex.org/W2062085002","https://openalex.org/W2124404372","https://openalex.org/W2136891917","https://openalex.org/W2154579312","https://openalex.org/W2161969291","https://openalex.org/W2162762921","https://openalex.org/W2170841223","https://openalex.org/W2295930631","https://openalex.org/W6682751323"],"related_works":["https://openalex.org/W2779573348","https://openalex.org/W1995536880","https://openalex.org/W4224879220","https://openalex.org/W4210781881","https://openalex.org/W2620723295","https://openalex.org/W4255221925","https://openalex.org/W2134786086","https://openalex.org/W3121973004","https://openalex.org/W2914711766","https://openalex.org/W3208266890"],"abstract_inverted_index":{"Traffic":[0],"Light":[1],"Detection(TLD)":[2],"and":[3,52,64,79,105,162,222],"understanding":[4],"their":[5],"state":[6,29,36,70,174],"semantics":[7],"at":[8],"intersections":[9],"plays":[10],"a":[11,58,197,203],"pivotal":[12],"role":[13],"in":[14,32,109,119,140,202],"driver":[15],"assistance":[16],"systems":[17],"and,":[18],"by":[19,92],"extension,":[20],"autonomous":[21],"vehicles.":[22],"Despite":[23],"of":[24,116,152,175,188,199],"several":[25,194],"reliable":[26],"traffic":[27,34,60,86,117,137,147,163,177],"light":[28,35,61,87,118,138,148,164,221],"detection":[30,63],"approaches":[31],"literature,":[33],"recognition":[37,71],"still":[38],"remains":[39],"an":[40],"open":[41],"problem":[42],"due":[43],"to":[44,111,133],"outdoor":[45],"perception":[46],"challenge":[47],"which":[48,73,98,131],"includes":[49],"occlusions,":[50],"illumination":[51,78],"scale":[53],"variations.":[54],"This":[55],"paper":[56],"presents":[57],"vision-based":[59],"structure":[62,139],"convolutional":[65],"neural":[66],"network":[67],"(CNN)":[68],"based":[69,95,216],"method,":[72,191],"is":[74,129],"robust":[75],"under":[76,196,219],"different":[77],"weather":[80,223],"conditions.":[81,224],"In":[82],"the":[83,113,135,141,146,176,186,189,210],"first":[84],"step,":[85],"candidate":[88,149],"regions":[89],"are":[90,99,157,166,179],"generated":[91],"performing":[93],"HSV":[94],"color":[96],"segmentation,":[97],"then":[100,180],"filtered":[101],"out":[102],"using":[103,168,182],"shape":[104],"area":[106],"analysis.":[107],"Further,":[108],"order":[110],"incorporate":[112],"structural":[114],"information":[115],"diverse":[120],"background":[121],"scenarios,":[122],"Maximally":[123],"Stable":[124],"Extremal":[125],"Region":[126],"(MSER)":[127],"approach":[128],"employed,":[130],"helps":[132],"localize":[134],"correct":[136],"image.":[142],"To":[143,184],"further":[144],"validate":[145],"regions,":[150],"Histogram":[151],"Oriented":[153],"Gradients":[154],"(HOG)":[155],"features":[156],"extracted":[158],"for":[159],"each":[160],"region":[161],"structures":[165],"validated":[167],"Support":[169],"Vector":[170],"Machine":[171],"(SVM).":[172],"The":[173],"lights":[178],"recognized":[181],"CNN.":[183],"evaluate":[185],"performance":[187],"proposed":[190,211],"we":[192],"present":[193],"results":[195],"variety":[198],"lighting":[200],"conditions":[201],"real-world":[204],"environment.":[205],"Experimental":[206],"result":[207],"shows":[208],"that":[209],"method":[212],"outperforms":[213],"other":[214],"vision":[215],"conventional":[217],"methods":[218],"varying":[220]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":16},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":12},{"year":2019,"cited_by_count":12},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":1}],"updated_date":"2026-04-03T22:45:19.894376","created_date":"2025-10-10T00:00:00"}