{"id":"https://openalex.org/W4402435496","doi":"https://doi.org/10.1109/tnnls.2024.3454063","title":"TFG-Net: A Text Feature-Guided Network for Small Traffic Sign Detection","display_name":"TFG-Net: A Text Feature-Guided Network for Small Traffic Sign Detection","publication_year":2024,"publication_date":"2024-09-11","ids":{"openalex":"https://openalex.org/W4402435496","doi":"https://doi.org/10.1109/tnnls.2024.3454063","pmid":"https://pubmed.ncbi.nlm.nih.gov/39259644"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2024.3454063","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3454063","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Xuesong Liu","orcid":"https://orcid.org/0009-0000-0277-0648"},"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":"Xuesong Liu","raw_affiliation_strings":["School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0000-0277-0648","affiliations":[{"raw_affiliation_string":"School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003969987","display_name":"Renxin Chu","orcid":"https://orcid.org/0000-0002-1668-238X"},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Renxin Chu","raw_affiliation_strings":["Harvard Medical School, Boston, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harvard Medical School, Boston, MA, USA","institution_ids":["https://openalex.org/I136199984"]}]},{"author_position":"last","author":{"id":null,"display_name":"Baolin Liu","orcid":"https://orcid.org/0000-0003-0975-2316"},"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":"Baolin Liu","raw_affiliation_strings":["School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-0975-2316","affiliations":[{"raw_affiliation_string":"School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0219,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.77208469,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"36","issue":"7","first_page":"13579","last_page":"13592"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9962999820709229,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9962999820709229,"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":0.9883999824523926,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9678999781608582,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/sign","display_name":"Sign (mathematics)","score":0.7509066462516785},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.7176718711853027},{"id":"https://openalex.org/keywords/traffic-sign","display_name":"Traffic sign","score":0.6532841920852661},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6192999482154846},{"id":"https://openalex.org/keywords/net","display_name":"Net (polyhedron)","score":0.6104117035865784},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46684014797210693},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35222291946411133},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07697165012359619},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.05808606743812561}],"concepts":[{"id":"https://openalex.org/C139676723","wikidata":"https://www.wikidata.org/wiki/Q1193832","display_name":"Sign (mathematics)","level":2,"score":0.7509066462516785},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.7176718711853027},{"id":"https://openalex.org/C2983860417","wikidata":"https://www.wikidata.org/wiki/Q170285","display_name":"Traffic sign","level":3,"score":0.6532841920852661},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6192999482154846},{"id":"https://openalex.org/C14166107","wikidata":"https://www.wikidata.org/wiki/Q253829","display_name":"Net (polyhedron)","level":2,"score":0.6104117035865784},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46684014797210693},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35222291946411133},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07697165012359619},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.05808606743812561},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2024.3454063","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3454063","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:39259644","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39259644","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":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1196410651","display_name":null,"funder_award_id":"FRF-MP-19-007","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1451794208","display_name":null,"funder_award_id":"U2133218","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1561159920","display_name":null,"funder_award_id":"FRF-MP-19-007","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G6559669898","display_name":null,"funder_award_id":"FRF-TP-20-065A1Z","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G8436104775","display_name":null,"funder_award_id":"2018YFB0204304","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8732108628","display_name":null,"funder_award_id":"FRF-TP-20-065A1Z","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"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W2005768981","https://openalex.org/W2102605133","https://openalex.org/W2193145675","https://openalex.org/W2276973678","https://openalex.org/W2479866714","https://openalex.org/W2625219738","https://openalex.org/W2791496413","https://openalex.org/W2886362581","https://openalex.org/W2896155169","https://openalex.org/W2962951509","https://openalex.org/W2963037989","https://openalex.org/W2963351448","https://openalex.org/W2964018263","https://openalex.org/W2985384565","https://openalex.org/W2989676862","https://openalex.org/W3004860639","https://openalex.org/W3014560200","https://openalex.org/W3018757597","https://openalex.org/W3034971973","https://openalex.org/W3084946993","https://openalex.org/W3096609285","https://openalex.org/W3106753828","https://openalex.org/W3107867277","https://openalex.org/W3121101473","https://openalex.org/W3157042932","https://openalex.org/W3157386596","https://openalex.org/W3159885298","https://openalex.org/W3172752666","https://openalex.org/W3213476061","https://openalex.org/W4221079664","https://openalex.org/W4285176535","https://openalex.org/W4293812210","https://openalex.org/W4308475787","https://openalex.org/W4312255851","https://openalex.org/W4312312588","https://openalex.org/W4312452284","https://openalex.org/W4312823573","https://openalex.org/W4318953592","https://openalex.org/W4323358415","https://openalex.org/W4386076325","https://openalex.org/W4386590230","https://openalex.org/W4386822527","https://openalex.org/W4389988788","https://openalex.org/W4390187137","https://openalex.org/W6750227808","https://openalex.org/W6784094891","https://openalex.org/W6792039502","https://openalex.org/W6802599522","https://openalex.org/W6873058455","https://openalex.org/W6945244495"],"related_works":["https://openalex.org/W2912321008","https://openalex.org/W1998607122","https://openalex.org/W2110143569","https://openalex.org/W2547328273","https://openalex.org/W746432122","https://openalex.org/W643638081","https://openalex.org/W4386159726","https://openalex.org/W1582770384","https://openalex.org/W2369781462","https://openalex.org/W564764569"],"abstract_inverted_index":{"Detecting":[0],"small":[1,36,46],"signs":[2,37,47,73],"in":[3],"complex":[4],"real-world":[5],"environments":[6],"remains":[7],"challenging":[8],"due":[9],"to":[10,30,77,118],"limited":[11],"feature":[12,43,103],"information":[13,44],"and":[14,74,99,113,122,150],"interference":[15],"from":[16,71],"other":[17,54],"objects.":[18,55],"In":[19],"this":[20],"article,":[21],"we":[22],"propose":[23],"a":[24,62,101,106],"novel":[25],"text":[26,63],"feature-guided":[27],"network":[28],"(TFG-Net)":[29],"improve":[31],"the":[32,35,42,51,57,72,78,83,90,132,141],"performance":[33],"of":[34,45,53,87,138],"detection":[38,64,80,85],"not":[39],"only":[40],"enhancing":[41],"but":[48],"also":[49],"avoiding":[50],"influence":[52],"As":[56],"name":[58],"suggests,":[59],"TFG-Net":[60,88,130],"incorporates":[61],"branch,":[65],"which":[66],"extracts":[67],"additional":[68],"textual":[69],"features":[70,98,115],"supplies":[75],"them":[76],"object":[79,84,157],"branch.":[81],"Furthermore,":[82],"branch":[86],"optimizes":[89],"backbone":[91],"network's":[92],"output":[93],"structure":[94],"by":[95],"merging":[96],"deep":[97],"introducing":[100],"high-resolution":[102],"layer.":[104],"Finally,":[105],"fusion":[107],"method":[108],"that":[109,128],"enhances":[110],"both":[111],"overall":[112],"local":[114],"is":[116],"proposed":[117],"fully":[119],"integrate":[120],"detailed":[121],"semantic":[123],"information.":[124],"Experimental":[125],"results":[126],"display":[127],"our":[129],"reaches":[131],"highest":[133],"mean":[134],"average":[135],"precision":[136],"(mAP)":[137],"92.5%":[139],"on":[140,148,152],"public":[142],"datasets":[143],"Tsinghua-Tencent":[144],"100K":[145],"(TT100K),":[146],"83.7%":[147],"CCTSDB2021,":[149],"79.1%":[151],"DFG,":[153],"surpassing":[154],"current":[155],"state-of-the-art":[156],"detectors.":[158]},"counts_by_year":[{"year":2025,"cited_by_count":5}],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}