{"id":"https://openalex.org/W2897583173","doi":"https://doi.org/10.1109/ijcnn.2018.8489623","title":"DeepSign: Deep Learning based Traffic Sign Recognition","display_name":"DeepSign: Deep Learning based Traffic Sign Recognition","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2897583173","doi":"https://doi.org/10.1109/ijcnn.2018.8489623","mag":"2897583173"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2018.8489623","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2018.8489623","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100659911","display_name":"Dong Li","orcid":"https://orcid.org/0000-0001-7369-1445"},"institutions":[{"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":"Dong Li","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"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/A5100624298","display_name":"Dongbin Zhao","orcid":"https://orcid.org/0000-0001-8218-9633"},"institutions":[{"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":["University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"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/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":"Yaran Chen","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049454999","display_name":"Qichao Zhang","orcid":"https://orcid.org/0000-0001-9747-391X"},"institutions":[{"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":"Qichao Zhang","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9987000226974487,"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"}},{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/traffic-sign-recognition","display_name":"Traffic sign recognition","score":0.8397729396820068},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7980873584747314},{"id":"https://openalex.org/keywords/traffic-sign","display_name":"Traffic sign","score":0.7607791423797607},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6946408152580261},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5645983815193176},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5613604187965393},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5479833483695984},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5302695035934448},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5169172286987305},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5168788433074951},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5112000107765198},{"id":"https://openalex.org/keywords/sign","display_name":"Sign (mathematics)","score":0.47186774015426636},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.454093873500824},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.431227445602417},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10230931639671326}],"concepts":[{"id":"https://openalex.org/C6528762","wikidata":"https://www.wikidata.org/wiki/Q1574298","display_name":"Traffic sign recognition","level":4,"score":0.8397729396820068},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7980873584747314},{"id":"https://openalex.org/C2983860417","wikidata":"https://www.wikidata.org/wiki/Q170285","display_name":"Traffic sign","level":3,"score":0.7607791423797607},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6946408152580261},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5645983815193176},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5613604187965393},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5479833483695984},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5302695035934448},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5169172286987305},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5168788433074951},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5112000107765198},{"id":"https://openalex.org/C139676723","wikidata":"https://www.wikidata.org/wiki/Q1193832","display_name":"Sign (mathematics)","level":2,"score":0.47186774015426636},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.454093873500824},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.431227445602417},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10230931639671326},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2018.8489623","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2018.8489623","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.4099999964237213,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1677182931","https://openalex.org/W1861492603","https://openalex.org/W1998871722","https://openalex.org/W2001412060","https://openalex.org/W2012742472","https://openalex.org/W2097117768","https://openalex.org/W2113650053","https://openalex.org/W2117539524","https://openalex.org/W2194775991","https://openalex.org/W2472350142","https://openalex.org/W2479866714","https://openalex.org/W2524008204","https://openalex.org/W2524771588","https://openalex.org/W2550190059","https://openalex.org/W2612445135","https://openalex.org/W2613718673","https://openalex.org/W2742332513","https://openalex.org/W2963150697","https://openalex.org/W3097096317","https://openalex.org/W3106250896","https://openalex.org/W3214102110","https://openalex.org/W4297775537","https://openalex.org/W6639102338","https://openalex.org/W6687483927","https://openalex.org/W6721476862","https://openalex.org/W6737664043","https://openalex.org/W6742309730","https://openalex.org/W6785652829","https://openalex.org/W6804270185"],"related_works":["https://openalex.org/W4299822940","https://openalex.org/W2279398222","https://openalex.org/W4311401716","https://openalex.org/W2773120646","https://openalex.org/W3011074480","https://openalex.org/W2982055638","https://openalex.org/W3156786002","https://openalex.org/W2732542196","https://openalex.org/W2059299633","https://openalex.org/W4221014278"],"abstract_inverted_index":{"This":[0],"paper":[1],"investigates":[2],"the":[3,28,41,51,73,76,81,86,90,93,98,103,109,115,118,123,127],"traffic":[4,29,67,87,128],"sign":[5,30,88,129],"recognition":[6,52,130],"task":[7,131],"with":[8],"deep":[9],"learning":[10],"methods.":[11],"The":[12,54,112],"proposed":[13,94,119],"algorithm":[14],"which":[15,64,84],"is":[16,56],"called":[17],"DeepSign":[18],"includes":[19],"three":[20],"modules:":[21],"a":[22,32,35,46,57],"detection":[23,60,105],"module":[24,37],"(PosNet)":[25],"for":[26,39,49],"locating":[27],"in":[31,132],"static":[33,91],"image,":[34,92],"classification":[36],"(PatchNet)":[38],"classifying":[40],"detected":[42],"image":[43],"patch,":[44],"and":[45,72,107],"temporal":[47,95],"filter":[48,96],"correcting":[50],"results.":[53],"PosNet":[55],"binary":[58],"object":[59],"convolution":[61],"neural":[62],"network":[63],"regards":[65],"all":[66],"signs":[68],"as":[69,75],"one":[70],"class":[71],"background":[74],"other":[77],"class.":[78],"Different":[79],"from":[80],"traditional":[82],"works":[83],"recognize":[85],"on":[89,126],"exploits":[97],"contextual":[99],"information":[100],"to":[101],"recover":[102],"missed":[104],"region":[106],"correct":[108],"false":[110],"classification.":[111],"experiments":[113],"validate":[114],"effectiveness":[116],"of":[117],"algorithm.":[120],"It":[121],"achieved":[122],"third":[124],"place":[125],"2017":[133],"China":[134],"intelligent":[135],"vehicle":[136],"future":[137],"challenge":[138],"(2017":[139],"CIVFC).":[140]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}