{"id":"https://openalex.org/W3004025639","doi":"https://doi.org/10.1142/s0218843020400079","title":"Traffic Sign Identification Using a Partially Cooperative Strategy in a Convolutional Neural Network","display_name":"Traffic Sign Identification Using a Partially Cooperative Strategy in a Convolutional Neural Network","publication_year":2020,"publication_date":"2020-01-31","ids":{"openalex":"https://openalex.org/W3004025639","doi":"https://doi.org/10.1142/s0218843020400079","mag":"3004025639"},"language":"en","primary_location":{"id":"doi:10.1142/s0218843020400079","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218843020400079","pdf_url":null,"source":{"id":"https://openalex.org/S17147961","display_name":"International Journal of Cooperative Information Systems","issn_l":"0218-8430","issn":["0218-8430","1793-6365"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Cooperative Information 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/A5101843546","display_name":"Hongbo Wang","orcid":"https://orcid.org/0000-0002-5408-7549"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hongbo Wang","raw_affiliation_strings":["School of Computer and Communication Engineering, Beijing Key Lab of Knowledge Engineering for Materials Science, University of Science and Technology Beijing, Xueyuan Road 30, Haidian Zone, Beijing 100083, P. R. China"],"raw_orcid":"https://orcid.org/0000-0002-5408-7549","affiliations":[{"raw_affiliation_string":"School of Computer and Communication Engineering, Beijing Key Lab of Knowledge Engineering for Materials Science, University of Science and Technology Beijing, Xueyuan Road 30, Haidian Zone, Beijing 100083, P. R. China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109301514","display_name":"Yulu Feng","orcid":null},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yulu Feng","raw_affiliation_strings":["School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, P. R. China","institution_ids":["https://openalex.org/I92403157"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101843546"],"corresponding_institution_ids":["https://openalex.org/I92403157"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.00927968,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"29","issue":"01n02","first_page":"2040007","last_page":"2040007"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9988999962806702,"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"}},"topics":[{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9988999962806702,"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"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9984999895095825,"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":0.9882000088691711,"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":0.9102420806884766},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7586421370506287},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5994049906730652},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5516975522041321},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4807474613189697},{"id":"https://openalex.org/keywords/traffic-sign","display_name":"Traffic sign","score":0.45066699385643005},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4390411972999573},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.4157174825668335},{"id":"https://openalex.org/keywords/sign","display_name":"Sign (mathematics)","score":0.3791942894458771},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3557438552379608},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34607994556427}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.9102420806884766},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7586421370506287},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5994049906730652},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5516975522041321},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4807474613189697},{"id":"https://openalex.org/C2983860417","wikidata":"https://www.wikidata.org/wiki/Q170285","display_name":"Traffic sign","level":3,"score":0.45066699385643005},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4390411972999573},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.4157174825668335},{"id":"https://openalex.org/C139676723","wikidata":"https://www.wikidata.org/wiki/Q1193832","display_name":"Sign (mathematics)","level":2,"score":0.3791942894458771},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3557438552379608},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34607994556427},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","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/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218843020400079","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218843020400079","pdf_url":null,"source":{"id":"https://openalex.org/S17147961","display_name":"International Journal of Cooperative Information Systems","issn_l":"0218-8430","issn":["0218-8430","1793-6365"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Cooperative Information Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8654819145","display_name":null,"funder_award_id":"61572074","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1978736542","https://openalex.org/W2011342602","https://openalex.org/W2097117768","https://openalex.org/W2103615355","https://openalex.org/W2108069432","https://openalex.org/W2112796928","https://openalex.org/W2117539524","https://openalex.org/W2125085157","https://openalex.org/W2132172482","https://openalex.org/W2165698076","https://openalex.org/W2188581537","https://openalex.org/W2194775991","https://openalex.org/W2523198174","https://openalex.org/W2791496413","https://openalex.org/W2807119280"],"related_works":["https://openalex.org/W746432122","https://openalex.org/W4386037136","https://openalex.org/W174788178","https://openalex.org/W637596653","https://openalex.org/W4309650776","https://openalex.org/W643638081","https://openalex.org/W1582770384","https://openalex.org/W4206608251","https://openalex.org/W3179972963","https://openalex.org/W3047972781"],"abstract_inverted_index":{"Recently,":[0],"deep":[1],"learning":[2],"has":[3],"introduced":[4],"new":[5],"prospects":[6],"to":[7,93,138],"numerous":[8],"practical":[9],"applications":[10],"such":[11],"as":[12],"image":[13],"recognition,":[14],"robot":[15],"navigation,":[16],"gene":[17],"engineering,":[18],"language":[19],"processing,":[20],"and":[21,32,64,111,132,146],"traffic":[22,139],"sign":[23,140],"identification.":[24],"Several":[25],"network":[26],"models":[27],"including":[28],"AlexNet,":[29],"VGGNet,":[30],"GoogLenet":[31],"ResNet,":[33],"have":[34],"achieved":[35],"milestone":[36],"contributions":[37],"while":[38],"relying":[39],"on":[40,143],"massive":[41],"computing":[42],"resources.":[43],"However,":[44],"when":[45],"faced":[46],"with":[47,76,87,136],"a":[48,77,82,98,130,144],"small":[49,110,145],"number":[50],"of":[51,58,109,129],"labeled":[52],"examples,":[53],"especially":[54],"in":[55,114],"the":[56,61,72,107,115,121,127],"case":[57],"unbalanced":[59,112],"datasets,":[60],"cumulative":[62],"error":[63],"time-consuming":[65],"convergence":[66],"reduce":[67],"their":[68],"efficacy.":[69],"Inspired":[70],"by":[71],"convolutional":[73,83],"output":[74],"layer":[75],"[Formula:":[78],"see":[79],"text]":[80],"kernel,":[81],"nonlinear":[84],"transfer":[85],"approach":[86],"partial":[88],"cooperating":[89],"(CNN-COL)":[90],"is":[91],"proposed":[92,122],"address":[94],"this":[95],"challenge.":[96],"Meanwhile,":[97],"novel":[99],"method":[100],"for":[101],"data":[102],"augmented":[103],"balance":[104],"can":[105,124],"enhance":[106],"influence":[108],"samples":[113],"CNN-COL.":[116],"Related":[117],"experiments":[118],"show":[119],"that":[120],"CNN-COL":[123],"effectively":[125],"improve":[126],"quality":[128],"dataset":[131],"achieve":[133],"superior":[134],"performance":[135],"respect":[137],"identification":[141],"based":[142],"type-unbalanced":[147],"dataset.":[148]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}