{"id":"https://openalex.org/W4391562142","doi":"https://doi.org/10.3390/s24030989","title":"YOLOv7-TS: A Traffic Sign Detection Model Based on Sub-Pixel Convolution and Feature Fusion","display_name":"YOLOv7-TS: A Traffic Sign Detection Model Based on Sub-Pixel Convolution and Feature Fusion","publication_year":2024,"publication_date":"2024-02-03","ids":{"openalex":"https://openalex.org/W4391562142","doi":"https://doi.org/10.3390/s24030989","pmid":"https://pubmed.ncbi.nlm.nih.gov/38339706"},"language":"en","primary_location":{"id":"doi:10.3390/s24030989","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24030989","pdf_url":"https://www.mdpi.com/1424-8220/24/3/989/pdf?version=1706942400","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/24/3/989/pdf?version=1706942400","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5008698127","display_name":"Shan Zhao","orcid":"https://orcid.org/0000-0002-3376-6649"},"institutions":[{"id":"https://openalex.org/I4210166499","display_name":"Henan Polytechnic University","ror":"https://ror.org/05vr1c885","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210166499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shan Zhao","raw_affiliation_strings":["School of Software, Henan Polytechnic University, Jiaozuo 454000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software, Henan Polytechnic University, Jiaozuo 454000, China","institution_ids":["https://openalex.org/I4210166499"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101296376","display_name":"Yang Yuan","orcid":"https://orcid.org/0009-0000-0056-6205"},"institutions":[{"id":"https://openalex.org/I4210166499","display_name":"Henan Polytechnic University","ror":"https://ror.org/05vr1c885","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210166499"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yang Yuan","raw_affiliation_strings":["School of Software, Henan Polytechnic University, Jiaozuo 454000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software, Henan Polytechnic University, Jiaozuo 454000, China","institution_ids":["https://openalex.org/I4210166499"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072620654","display_name":"Xuan Wu","orcid":"https://orcid.org/0000-0002-1640-6043"},"institutions":[{"id":"https://openalex.org/I4210166499","display_name":"Henan Polytechnic University","ror":"https://ror.org/05vr1c885","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210166499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuan Wu","raw_affiliation_strings":["School of Software, Henan Polytechnic University, Jiaozuo 454000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software, Henan Polytechnic University, Jiaozuo 454000, China","institution_ids":["https://openalex.org/I4210166499"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004290242","display_name":"Yunlei Wang","orcid":"https://orcid.org/0009-0007-1819-5212"},"institutions":[{"id":"https://openalex.org/I4210166499","display_name":"Henan Polytechnic University","ror":"https://ror.org/05vr1c885","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210166499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunlei Wang","raw_affiliation_strings":["School of Software, Henan Polytechnic University, Jiaozuo 454000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software, Henan Polytechnic University, Jiaozuo 454000, China","institution_ids":["https://openalex.org/I4210166499"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062946377","display_name":"Fukai Zhang","orcid":"https://orcid.org/0000-0002-7378-3478"},"institutions":[{"id":"https://openalex.org/I4210166499","display_name":"Henan Polytechnic University","ror":"https://ror.org/05vr1c885","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210166499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fukai Zhang","raw_affiliation_strings":["School of Software, Henan Polytechnic University, Jiaozuo 454000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software, Henan Polytechnic University, Jiaozuo 454000, China","institution_ids":["https://openalex.org/I4210166499"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5101296376"],"corresponding_institution_ids":["https://openalex.org/I4210166499"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":4.7518,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.96013972,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"24","issue":"3","first_page":"989","last_page":"989"},"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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9951000213623047,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"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":0.9801999926567078,"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/computer-science","display_name":"Computer science","score":0.7087507247924805},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.7051404118537903},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6818503141403198},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.639634907245636},{"id":"https://openalex.org/keywords/traffic-sign","display_name":"Traffic sign","score":0.5468111634254456},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.534588098526001},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5254310965538025},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5166445374488831},{"id":"https://openalex.org/keywords/traffic-sign-recognition","display_name":"Traffic sign recognition","score":0.5148293375968933},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4993906021118164},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4970555603504181},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4434610903263092},{"id":"https://openalex.org/keywords/sign","display_name":"Sign (mathematics)","score":0.43079665303230286},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.42136555910110474},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1771579086780548},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11252176761627197}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7087507247924805},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.7051404118537903},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6818503141403198},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.639634907245636},{"id":"https://openalex.org/C2983860417","wikidata":"https://www.wikidata.org/wiki/Q170285","display_name":"Traffic sign","level":3,"score":0.5468111634254456},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.534588098526001},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5254310965538025},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5166445374488831},{"id":"https://openalex.org/C6528762","wikidata":"https://www.wikidata.org/wiki/Q1574298","display_name":"Traffic sign recognition","level":4,"score":0.5148293375968933},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4993906021118164},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4970555603504181},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4434610903263092},{"id":"https://openalex.org/C139676723","wikidata":"https://www.wikidata.org/wiki/Q1193832","display_name":"Sign (mathematics)","level":2,"score":0.43079665303230286},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.42136555910110474},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1771579086780548},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11252176761627197},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"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/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/s24030989","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24030989","pdf_url":"https://www.mdpi.com/1424-8220/24/3/989/pdf?version=1706942400","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:38339706","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38339706","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:10857214","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10857214","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10857214/pdf/sensors-24-00989.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:2bec008d62214dd2bff1a4845895ed06","is_oa":false,"landing_page_url":"https://doaj.org/article/2bec008d62214dd2bff1a4845895ed06","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 24, Iss 3, p 989 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/s24030989","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24030989","pdf_url":"https://www.mdpi.com/1424-8220/24/3/989/pdf?version=1706942400","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1522100992","display_name":null,"funder_award_id":"61602157","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8642817995","display_name":null,"funder_award_id":"202102210167","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":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4391562142.pdf"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W127100323","https://openalex.org/W1536680647","https://openalex.org/W1977610018","https://openalex.org/W2005768981","https://openalex.org/W2014852133","https://openalex.org/W2016740225","https://openalex.org/W2077753765","https://openalex.org/W2102605133","https://openalex.org/W2109255472","https://openalex.org/W2110591696","https://openalex.org/W2157735336","https://openalex.org/W2163605009","https://openalex.org/W2193145675","https://openalex.org/W2476548250","https://openalex.org/W2479866714","https://openalex.org/W2565639579","https://openalex.org/W2570343428","https://openalex.org/W2613718673","https://openalex.org/W2625219738","https://openalex.org/W2791496413","https://openalex.org/W2905527144","https://openalex.org/W2924873663","https://openalex.org/W2955747520","https://openalex.org/W2962721361","https://openalex.org/W2963037989","https://openalex.org/W2963163009","https://openalex.org/W2963351448","https://openalex.org/W2963604034","https://openalex.org/W2963857746","https://openalex.org/W2964241181","https://openalex.org/W3004860639","https://openalex.org/W3034307881","https://openalex.org/W3034971973","https://openalex.org/W3042011474","https://openalex.org/W3106250896","https://openalex.org/W3107867277","https://openalex.org/W3125534091","https://openalex.org/W3128954682","https://openalex.org/W3167976421","https://openalex.org/W3210586215","https://openalex.org/W4317486508","https://openalex.org/W4318953592","https://openalex.org/W4386071964","https://openalex.org/W4386076325","https://openalex.org/W4390075009","https://openalex.org/W6680535452","https://openalex.org/W6684191040","https://openalex.org/W6945244495"],"related_works":["https://openalex.org/W4382897155","https://openalex.org/W4379231512","https://openalex.org/W4283820116","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":{"In":[0],"recent":[1],"years,":[2],"significant":[3,185],"progress":[4],"has":[5,28],"been":[6],"witnessed":[7],"in":[8,19,43,191],"the":[9,20,34,52,84,88,107,130,136,153,158,192,202,205],"field":[10,21],"of":[11,22,54,87,139,181,187,204],"deep":[12],"learning-based":[13],"object":[14,23,36],"detection.":[15],"As":[16],"a":[17,65,97,112,143,178,184],"subtask":[18],"detection,":[24],"traffic":[25,40,66,166],"sign":[26,41,67,167],"detection":[27,37,42,59,68],"great":[29],"potential":[30],"for":[31,39,197],"development.":[32],"However,":[33],"existing":[35],"methods":[38],"real-world":[44],"scenes":[45],"are":[46],"plagued":[47],"by":[48],"issues":[49],"such":[50],"as":[51],"omission":[53],"small":[55,140],"objects":[56],"and":[57,80,96,134,171,189],"low":[58],"accuracies.":[60],"To":[61],"address":[62],"these":[63],"issues,":[64],"model":[69],"named":[70],"YOLOv7-Traffic":[71],"Sign":[72],"(YOLOv7-TS)":[73],"is":[74,94,103,118,149,162],"proposed":[75,206],"based":[76],"on":[77,164],"sub-pixel":[78,89],"convolution":[79,90],"feature":[81,127,131],"fusion.":[82],"Firstly,":[83],"up-sampling":[85],"capability":[86],"integrating":[91],"channel":[92,108],"dimension":[93],"harnessed":[95],"Feature":[98,145],"Map":[99],"Extraction":[100],"Module":[101,147],"(FMEM)":[102],"devised":[104],"to":[105,120,151],"mitigate":[106],"information":[109,123],"loss.":[110],"Furthermore,":[111],"Multi-feature":[113],"Interactive":[114],"Fusion":[115],"Network":[116],"(MIFNet)":[117],"constructed":[119],"facilitate":[121],"enhanced":[122],"interaction":[124],"among":[125],"all":[126],"layers,":[128],"improving":[129],"fusion":[132],"effectiveness":[133,203],"strengthening":[135],"perception":[137],"ability":[138],"objects.":[141],"Moreover,":[142],"Deep":[144],"Enhancement":[146],"(DFEM)":[148],"established":[150],"accelerate":[152],"pooling":[154],"process":[155],"while":[156],"enriching":[157],"highest-layer":[159],"feature.":[160],"YOLOv7-TS":[161],"evaluated":[163],"two":[165],"datasets,":[168],"namely":[169],"CCTSDB2021":[170],"TT100K.":[172],"Compared":[173],"with":[174,177],"YOLOv7,":[175],"YOLOv7-TS,":[176],"smaller":[179],"number":[180],"parameters,":[182],"achieves":[183],"enhancement":[186],"3.63%":[188],"2.68%":[190],"mean":[193],"Average":[194],"Precision":[195],"(mAP)":[196],"each":[198],"respective":[199],"dataset,":[200],"proving":[201],"model.":[207]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":4}],"updated_date":"2026-07-04T07:58:01.006859","created_date":"2025-10-10T00:00:00"}