{"id":"https://openalex.org/W4402351416","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650260","title":"TSD-YOLOv5: A traffic sign recognition algorithm based on improved YOLOv5","display_name":"TSD-YOLOv5: A traffic sign recognition algorithm based on improved YOLOv5","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4402351416","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650260"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn60899.2024.10650260","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn60899.2024.10650260","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 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/A5005533609","display_name":"Kong Geng","orcid":null},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Geng Kong","raw_affiliation_strings":["Xinjiang University,School of Software,Urumqi,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xinjiang University,School of Software,Urumqi,China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071338243","display_name":"Qing Yu","orcid":"https://orcid.org/0000-0003-2513-2969"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qing Yu","raw_affiliation_strings":["Xinjiang University,School of Computer Science and Technology,Urumqi,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xinjiang University,School of Computer Science and Technology,Urumqi,China","institution_ids":["https://openalex.org/I96908189"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I96908189"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.35007952,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"28","issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12707","display_name":"Vehicle License Plate Recognition","score":0.9997000098228455,"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":0.9997000098228455,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9994999766349792,"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":0.9968000054359436,"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/computer-science","display_name":"Computer science","score":0.7162529230117798},{"id":"https://openalex.org/keywords/traffic-sign-recognition","display_name":"Traffic sign recognition","score":0.601587176322937},{"id":"https://openalex.org/keywords/traffic-sign","display_name":"Traffic sign","score":0.5371772646903992},{"id":"https://openalex.org/keywords/sign","display_name":"Sign (mathematics)","score":0.5126249194145203},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4459008574485779},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3839500844478607},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3628841042518616},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11428529024124146}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7162529230117798},{"id":"https://openalex.org/C6528762","wikidata":"https://www.wikidata.org/wiki/Q1574298","display_name":"Traffic sign recognition","level":4,"score":0.601587176322937},{"id":"https://openalex.org/C2983860417","wikidata":"https://www.wikidata.org/wiki/Q170285","display_name":"Traffic sign","level":3,"score":0.5371772646903992},{"id":"https://openalex.org/C139676723","wikidata":"https://www.wikidata.org/wiki/Q1193832","display_name":"Sign (mathematics)","level":2,"score":0.5126249194145203},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4459008574485779},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3839500844478607},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3628841042518616},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11428529024124146},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn60899.2024.10650260","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn60899.2024.10650260","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"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":39,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2102605133","https://openalex.org/W2185813266","https://openalex.org/W2193145675","https://openalex.org/W2295198236","https://openalex.org/W2559265382","https://openalex.org/W2570343428","https://openalex.org/W2596537588","https://openalex.org/W2963037989","https://openalex.org/W2963150697","https://openalex.org/W3018757597","https://openalex.org/W3094611981","https://openalex.org/W3106250896","https://openalex.org/W3121101473","https://openalex.org/W3153632221","https://openalex.org/W3184439416","https://openalex.org/W3192805063","https://openalex.org/W3195809468","https://openalex.org/W4205306821","https://openalex.org/W4206754644","https://openalex.org/W4214700196","https://openalex.org/W4220773165","https://openalex.org/W4224053701","https://openalex.org/W4281678301","https://openalex.org/W4283748547","https://openalex.org/W4293584584","https://openalex.org/W4318255578","https://openalex.org/W4319600111","https://openalex.org/W4361003804","https://openalex.org/W4381433243","https://openalex.org/W4381938474","https://openalex.org/W4383559398","https://openalex.org/W4386047745","https://openalex.org/W6620707391","https://openalex.org/W6750227808","https://openalex.org/W6777046832","https://openalex.org/W6798838024","https://openalex.org/W6931202655","https://openalex.org/W6945244495"],"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":{"A":[0],"traffic":[1,23,28,43,47,66,147,155,194,212,239,258],"sign":[2,29,44,67,195,213,259],"recognition":[3,30,37,68,152,184,236,260],"system":[4],"is":[5,81,129,162,190,203,206,241],"a":[6,21,65,124,158],"key":[7],"component":[8],"in":[9,89,231],"real-world":[10],"applications":[11],"such":[12,34],"as":[13,35],"automated":[14],"driving":[15],"or":[16],"assisted":[17],"driver":[18],"driving.":[19],"In":[20],"complex":[22],"environment,":[24],"the":[25,73,77,90,96,101,106,109,116,121,132,139,151,166,171,178,193,200,209,221,228,251],"field":[26],"of":[27,87,105,120,135,146,154,177,254],"can":[31],"face":[32],"problems":[33],"low":[36],"accuracy":[38,153],"due":[39],"to":[40,54,100,137,164],"less":[41],"distinctive":[42],"features,":[45],"and":[46,56,103,114,141,174,199,216,249],"signs":[48],"with":[49],"smaller":[50],"targets":[51],"are":[52],"easy":[53],"miss":[55],"misdetect.":[57],"To":[58],"address":[59],"these":[60],"problems,":[61],"this":[62,232],"paper":[63,233],"proposes":[64],"algorithm":[69,188],"TSD-YOLOv5":[70,189,229],"based":[71],"on":[72,192,246],"improved":[74,187],"YOLOv5.":[75,223],"First,":[76],"loss":[78,110],"function":[79,111],"design":[80],"optimized":[82],"by":[83],"using":[84],"WISE-IoU":[85],"instead":[86],"CIoU":[88],"original":[91,222],"YOLOv5,":[92],"which":[93,149,169,205],"adaptively":[94],"adjusts":[95],"IoU":[97],"weights":[98],"according":[99],"size":[102],"shape":[104],"target,":[107],"making":[108],"more":[112,125,242],"balanced":[113],"improving":[115],"overall":[117],"detection":[118,214],"performance":[119,237],"model.":[122],"Secondly,":[123],"efficient":[126],"decoupling":[127],"head":[128],"fused":[130],"into":[131],"Head":[133],"part":[134],"YOLOv5":[136],"extract":[138],"location":[140],"category":[142],"information":[143],"feature":[144],"branches":[145],"signs,":[148,240],"improves":[150],"signs.":[156],"Finally,":[157],"new":[159],"C3-FN":[160],"module":[161],"proposed":[163,230],"replace":[165],"C3":[167],"module,":[168],"reduces":[170],"computational":[172],"redundancy":[173],"parameter":[175],"quantity":[176],"model":[179],"without":[180],"losing":[181],"too":[182],"much":[183],"effect.":[185],"The":[186,224],"tested":[191],"public":[196],"dataset":[197],"TT100K,":[198],"mAP":[201],"value":[202],"83.7%,":[204],"higher":[207,219],"than":[208,220],"current":[210],"mainstream":[211],"model,":[215],"also":[217],"3.8%":[218],"results":[225],"show":[226],"that":[227],"has":[234],"excellent":[235],"for":[238,244,257],"suitable":[243],"deployment":[245],"intelligent":[247,255],"devices,":[248],"meets":[250],"real-time":[252],"demand":[253],"vehicles":[256],"tasks.":[261]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}