{"id":"https://openalex.org/W4387385605","doi":"https://doi.org/10.1109/access.2023.3322371","title":"UCN-YOLOv5: Traffic Sign Object Detection Algorithm Based on Deep Learning","display_name":"UCN-YOLOv5: Traffic Sign Object Detection Algorithm Based on Deep Learning","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4387385605","doi":"https://doi.org/10.1109/access.2023.3322371"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3322371","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3322371","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2023.3322371","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007630964","display_name":"Peilin Liu","orcid":"https://orcid.org/0009-0009-6377-6862"},"institutions":[{"id":"https://openalex.org/I20942203","display_name":"Hainan University","ror":"https://ror.org/03q648j11","country_code":"CN","type":"education","lineage":["https://openalex.org/I20942203"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Peilin Liu","raw_affiliation_strings":["Internet Information Retrieval Major Laboratory, Hainan Province School of Information and Communication Engineering, Hainan University, Haikou, China","Internet Information Retrieval Major Laboratory of Hainan Province School of Information and Communication Engineering Hainan University Haikou, China"],"raw_orcid":"https://orcid.org/0009-0009-6377-6862","affiliations":[{"raw_affiliation_string":"Internet Information Retrieval Major Laboratory, Hainan Province School of Information and Communication Engineering, Hainan University, Haikou, China","institution_ids":["https://openalex.org/I20942203"]},{"raw_affiliation_string":"Internet Information Retrieval Major Laboratory of Hainan Province School of Information and Communication Engineering Hainan University Haikou, China","institution_ids":["https://openalex.org/I20942203"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026494579","display_name":"Zhaoyang Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I20942203","display_name":"Hainan University","ror":"https://ror.org/03q648j11","country_code":"CN","type":"education","lineage":["https://openalex.org/I20942203"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaoyang Xie","raw_affiliation_strings":["Internet Information Retrieval Major Laboratory, Hainan Province School of Information and Communication Engineering, Hainan University, Haikou, China","Internet Information Retrieval Major Laboratory of Hainan Province School of Information and Communication Engineering Hainan University Haikou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Internet Information Retrieval Major Laboratory, Hainan Province School of Information and Communication Engineering, Hainan University, Haikou, China","institution_ids":["https://openalex.org/I20942203"]},{"raw_affiliation_string":"Internet Information Retrieval Major Laboratory of Hainan Province School of Information and Communication Engineering Hainan University Haikou, China","institution_ids":["https://openalex.org/I20942203"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025359536","display_name":"Taijun Li","orcid":null},"institutions":[{"id":"https://openalex.org/I20942203","display_name":"Hainan University","ror":"https://ror.org/03q648j11","country_code":"CN","type":"education","lineage":["https://openalex.org/I20942203"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Taijun Li","raw_affiliation_strings":["Internet Information Retrieval Major Laboratory, Hainan Province School of Information and Communication Engineering, Hainan University, Haikou, China","Internet Information Retrieval Major Laboratory of Hainan Province School of Information and Communication Engineering Hainan University Haikou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Internet Information Retrieval Major Laboratory, Hainan Province School of Information and Communication Engineering, Hainan University, Haikou, China","institution_ids":["https://openalex.org/I20942203"]},{"raw_affiliation_string":"Internet Information Retrieval Major Laboratory of Hainan Province School of Information and Communication Engineering Hainan University Haikou, China","institution_ids":["https://openalex.org/I20942203"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5007630964"],"corresponding_institution_ids":["https://openalex.org/I20942203"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":4.0536,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.9539701,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"11","issue":null,"first_page":"110039","last_page":"110050"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9991999864578247,"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":0.9991999864578247,"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":0.9962999820709229,"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":0.9940999746322632,"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","display_name":"Traffic sign","score":0.831790030002594},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7943387031555176},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6640632748603821},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5682195425033569},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5392794013023376},{"id":"https://openalex.org/keywords/sign","display_name":"Sign (mathematics)","score":0.5377957820892334},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5301386117935181},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5092259645462036},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.47151410579681396},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.44647231698036194},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4293903410434723},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3816443979740143},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3518609404563904},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10127860307693481}],"concepts":[{"id":"https://openalex.org/C2983860417","wikidata":"https://www.wikidata.org/wiki/Q170285","display_name":"Traffic sign","level":3,"score":0.831790030002594},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7943387031555176},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6640632748603821},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5682195425033569},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5392794013023376},{"id":"https://openalex.org/C139676723","wikidata":"https://www.wikidata.org/wiki/Q1193832","display_name":"Sign (mathematics)","level":2,"score":0.5377957820892334},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5301386117935181},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5092259645462036},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.47151410579681396},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44647231698036194},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4293903410434723},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3816443979740143},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3518609404563904},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10127860307693481},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2023.3322371","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3322371","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:7a8f8068dc2d4156a3337fbbcf1baea3","is_oa":true,"landing_page_url":"https://doaj.org/article/7a8f8068dc2d4156a3337fbbcf1baea3","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 11, Pp 110039-110050 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3322371","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3322371","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W2067713319","https://openalex.org/W2102605133","https://openalex.org/W2117876524","https://openalex.org/W2126628495","https://openalex.org/W2479866714","https://openalex.org/W2765407302","https://openalex.org/W2884585870","https://openalex.org/W2919115004","https://openalex.org/W2962951509","https://openalex.org/W2963037989","https://openalex.org/W2970268874","https://openalex.org/W2982083293","https://openalex.org/W2996919757","https://openalex.org/W3009142993","https://openalex.org/W3014560200","https://openalex.org/W3025800305","https://openalex.org/W3118003871","https://openalex.org/W3129305243","https://openalex.org/W3177052299","https://openalex.org/W4214700196","https://openalex.org/W4293584584","https://openalex.org/W4312183515","https://openalex.org/W4312443924","https://openalex.org/W4313506322","https://openalex.org/W4362707005","https://openalex.org/W6745136726","https://openalex.org/W6753412334","https://openalex.org/W6790804480","https://openalex.org/W6851743980","https://openalex.org/W6945244495"],"related_works":["https://openalex.org/W2110143569","https://openalex.org/W2547328273","https://openalex.org/W746432122","https://openalex.org/W174788178","https://openalex.org/W637596653","https://openalex.org/W643638081","https://openalex.org/W4221037879","https://openalex.org/W1582770384","https://openalex.org/W2369781462","https://openalex.org/W564764569"],"abstract_inverted_index":{"Traffic":[0],"sign":[1,26,217,230],"detection":[2,22,149,167,227],"plays":[3],"an":[4],"important":[5,222],"role":[6],"in":[7,94,113,190,239],"traffic":[8,11,25,114,155,216,229],"safety":[9],"and":[10,18,21,66,73,187,200,214,232],"management.":[12],"In":[13],"view":[14],"of":[15,24,37,52,59,70,85,105,125,151,228],"the":[16,35,48,56,60,67,80,86,95,103,132,138,148,159,171,179,191,205,212,225],"complex":[17],"changeable":[19],"environment":[20],"accuracy":[23],"detection,":[27,231],"this":[28],"paper":[29],"proposes":[30],"UCN-YOLOv5":[31],"model":[32,39,153,173],"based":[33],"on":[34,158,211],"framework":[36],"YOLOv5.This":[38],"first":[40],"replaces":[41],"a":[42,99,142],"new":[43],"backbone":[44],"network,":[45],"which":[46,120,145],"uses":[47],"core":[49],"module":[50,69,92],"RSU":[51],"U2Net":[53],"to":[54,78,123,130,136,141],"enhance":[55],"feature":[57],"extraction":[58,104],"network.":[61],"Then,":[62],"ConvNeXt-V2":[63],"is":[64,76,121,128,195],"integrated,":[65],"C3":[68],"its":[71],"Block":[72],"YOLOv5":[74],"network":[75],"used":[77],"construct":[79],"C3_CN2":[81],"structure.":[82],"The":[83],"utilization":[84],"proposed":[87],"lightweight":[88],"receptive":[89,106],"field":[90,107],"attention":[91],"LPFAConv":[93],"Head":[96],"section":[97],"represents":[98],"potential":[100],"enhancement":[101],"for":[102,110,154,224,236],"features.":[108],"Finally,":[109],"small":[111],"targets":[112,124],"signs,":[115],"Normalized":[116],"Wasserstein":[117],"Distance":[118],"(NWD),":[119],"insensitive":[122],"different":[126],"scales,":[127],"added":[129],"calculate":[131],"position":[133],"loss":[134],"function":[135],"replace":[137],"IoU":[139],"metric":[140],"certain":[143],"extent,":[144],"further":[146],"improves":[147,178],"ability":[150],"our":[152],"signs.":[156],"Experiments":[157],"TT100K":[160],"dataset":[161],"show":[162],"that":[163],"UCNYOLOv5":[164],"has":[165,221,233],"excellent":[166],"performance.":[168],"Compared":[169],"with":[170],"baseline":[172],"(Y0Lov5s,":[174],"YOLOV5m,":[175],"YOLOV5l),":[176],"it":[177,194],"Map.5":[180],"index":[181],"by":[182],"5.9":[183],"%,":[184,197],"4.9":[185],"%":[186,199,202],"4.6":[188],"%;":[189],"Map.5:.95":[192],"index,":[193],"4.4":[196],"3.5":[198],"2.8":[201],"better.":[203],"Moreover,":[204],"enhanced":[206],"algorithm":[207],"demonstrated":[208],"favorable":[209],"performance":[210],"LISA":[213],"CCTSDB2021":[215],"datasets.":[218],"This":[219],"research":[220,238],"value":[223],"accurate":[226],"guiding":[234],"significance":[235],"in-depth":[237],"related":[240],"fields.":[241]},"counts_by_year":[{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}