{"id":"https://openalex.org/W2552460741","doi":"https://doi.org/10.1109/iscit.2016.7751612","title":"The research on traffic sign recognition based on deep learning","display_name":"The research on traffic sign recognition based on deep learning","publication_year":2016,"publication_date":"2016-09-01","ids":{"openalex":"https://openalex.org/W2552460741","doi":"https://doi.org/10.1109/iscit.2016.7751612","mag":"2552460741"},"language":"en","primary_location":{"id":"doi:10.1109/iscit.2016.7751612","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscit.2016.7751612","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 16th International Symposium on Communications and Information Technologies (ISCIT)","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/A5100369857","display_name":"Chen Li","orcid":"https://orcid.org/0000-0002-6475-3146"},"institutions":[{"id":"https://openalex.org/I75689368","display_name":"Communication University of China","ror":"https://ror.org/04facbs33","country_code":"CN","type":"education","lineage":["https://openalex.org/I75689368"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Li","raw_affiliation_strings":["Communication University of China, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Communication University of China, Beijing, China","institution_ids":["https://openalex.org/I75689368"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017431996","display_name":"Cheng Yang","orcid":"https://orcid.org/0000-0002-3858-1328"},"institutions":[{"id":"https://openalex.org/I75689368","display_name":"Communication University of China","ror":"https://ror.org/04facbs33","country_code":"CN","type":"education","lineage":["https://openalex.org/I75689368"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Yang","raw_affiliation_strings":["Communication University of China, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Communication University of China, Beijing, China","institution_ids":["https://openalex.org/I75689368"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.62,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.91792135,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"5","issue":null,"first_page":"156","last_page":"161"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12707","display_name":"Vehicle License Plate Recognition","score":0.9965000152587891,"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"}},"topics":[{"id":"https://openalex.org/T12707","display_name":"Vehicle License Plate Recognition","score":0.9965000152587891,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9866999983787537,"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":0.9850999712944031,"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/feature-extraction","display_name":"Feature extraction","score":0.769026517868042},{"id":"https://openalex.org/keywords/traffic-sign-recognition","display_name":"Traffic sign recognition","score":0.7652883529663086},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6521265506744385},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5511587858200073},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5001521110534668},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49884510040283203},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.49530473351478577},{"id":"https://openalex.org/keywords/traffic-sign","display_name":"Traffic sign","score":0.4762963354587555},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4295761287212372},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4265037775039673},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38124749064445496},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.24328097701072693},{"id":"https://openalex.org/keywords/sign","display_name":"Sign (mathematics)","score":0.19963738322257996},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.1937156319618225}],"concepts":[{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.769026517868042},{"id":"https://openalex.org/C6528762","wikidata":"https://www.wikidata.org/wiki/Q1574298","display_name":"Traffic sign recognition","level":4,"score":0.7652883529663086},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6521265506744385},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5511587858200073},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5001521110534668},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49884510040283203},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.49530473351478577},{"id":"https://openalex.org/C2983860417","wikidata":"https://www.wikidata.org/wiki/Q170285","display_name":"Traffic sign","level":3,"score":0.4762963354587555},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4295761287212372},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4265037775039673},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38124749064445496},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.24328097701072693},{"id":"https://openalex.org/C139676723","wikidata":"https://www.wikidata.org/wiki/Q1193832","display_name":"Sign (mathematics)","level":2,"score":0.19963738322257996},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.1937156319618225},{"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/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscit.2016.7751612","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscit.2016.7751612","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 16th International Symposium on Communications and Information Technologies (ISCIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.8399999737739563,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W132579780","https://openalex.org/W177847060","https://openalex.org/W1112996028","https://openalex.org/W1568931347","https://openalex.org/W1835073532","https://openalex.org/W1950329054","https://openalex.org/W1966659765","https://openalex.org/W2012728588","https://openalex.org/W2013139595","https://openalex.org/W2027560951","https://openalex.org/W2036161627","https://openalex.org/W2046812143","https://openalex.org/W2072056580","https://openalex.org/W2076063813","https://openalex.org/W2080140413","https://openalex.org/W2080239434","https://openalex.org/W2165955226","https://openalex.org/W2165966284","https://openalex.org/W2188343820","https://openalex.org/W2225763131","https://openalex.org/W2244865232","https://openalex.org/W2317354861","https://openalex.org/W2351667571","https://openalex.org/W2403529265","https://openalex.org/W2405487445","https://openalex.org/W2519656470","https://openalex.org/W4294620746","https://openalex.org/W6607232846","https://openalex.org/W6638882668","https://openalex.org/W6684713526","https://openalex.org/W6687187739","https://openalex.org/W6690919820","https://openalex.org/W7033508467"],"related_works":["https://openalex.org/W4382897155","https://openalex.org/W4283820116","https://openalex.org/W4379231512","https://openalex.org/W4378699879","https://openalex.org/W3128164723","https://openalex.org/W4286647459","https://openalex.org/W2899819381","https://openalex.org/W2557202782","https://openalex.org/W3215426395","https://openalex.org/W4382176313"],"abstract_inverted_index":{"With":[0],"the":[1,8,20,28,48,57,68,78,82,88,119,134,143],"further":[2],"and":[3,10,40,50,63,73,84,107,128,139],"faster":[4],"urbanization,":[5],"here":[6],"come":[7],"advent":[9],"development":[11,74],"of":[12,19,27,35,52,81,87,113,124],"intelligent":[13,29],"public":[14],"transportation":[15],"system.":[16,43],"The":[17,44,109],"identification":[18,51,98],"traffic":[21,53,60,89,114],"signs,":[22,90],"as":[23],"a":[24,33],"key":[25],"component":[26],"transit":[30],"system,":[31],"has":[32,145],"prospect":[34],"widespread":[36],"use":[37],"in":[38],"self-driving":[39],"driver":[41],"assistance":[42],"paper":[45],"focuses":[46],"on":[47,56,59,95,137],"classification":[49],"signs":[54,61,97,115],"based":[55,136],"researches":[58],"home":[62],"abroad":[64],"which":[65],"also":[66],"include":[67],"status":[69],"quo,":[70],"technological":[71],"problems":[72],"tendency.":[75],"Combined":[76],"with":[77,118,133],"significant":[79],"features":[80],"shape":[83],"internal":[85],"structure":[86],"three":[91],"new":[92],"feature-based":[93],"algorithms":[94,120,135],"road":[96],"have":[99],"been":[100],"implemented,":[101],"including":[102],"image":[103],"pretreatment,":[104],"feature":[105,110,141],"extraction":[106,111],"classifier.":[108],"work":[112],"is":[116],"conducted":[117],"using":[121],"an":[122],"integration":[123],"Deep":[125],"Boltzmann":[126],"Machines":[127],"Canonical":[129],"Correlation":[130],"Analysis.":[131],"Compared":[132],"HOG":[138],"LBP":[140],"extraction,":[142],"DBM-CCA":[144],"higher":[146],"accuracy.":[147]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
