{"id":"https://openalex.org/W7128638925","doi":"https://doi.org/10.1109/icves65691.2025.11376052","title":"A Study of Traffic Sign Information Acquisition Methods for Safe Bicycle Navigation","display_name":"A Study of Traffic Sign Information Acquisition Methods for Safe Bicycle Navigation","publication_year":2025,"publication_date":"2025-10-27","ids":{"openalex":"https://openalex.org/W7128638925","doi":"https://doi.org/10.1109/icves65691.2025.11376052"},"language":null,"primary_location":{"id":"doi:10.1109/icves65691.2025.11376052","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icves65691.2025.11376052","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","raw_type":"proceedings-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/A5111379084","display_name":"T. Nagaosa","orcid":null},"institutions":[{"id":"https://openalex.org/I203021718","display_name":"Kanto Gakuin University","ror":"https://ror.org/041bf1s37","country_code":"JP","type":"education","lineage":["https://openalex.org/I203021718"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Tomotaka Nagaosa","raw_affiliation_strings":["Kanto Gakuin University,College of Science and Engineering,Yokohama Kanagawa,Japan"],"affiliations":[{"raw_affiliation_string":"Kanto Gakuin University,College of Science and Engineering,Yokohama Kanagawa,Japan","institution_ids":["https://openalex.org/I203021718"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5125638671","display_name":"Akihiro Tada","orcid":null},"institutions":[{"id":"https://openalex.org/I4210124472","display_name":"Dream Laboratory (United Kingdom)","ror":"https://ror.org/035wa3p49","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210124472"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Akihiro Tada","raw_affiliation_strings":["Dream Career Co.,Ltd.,Tokyo,Japan"],"affiliations":[{"raw_affiliation_string":"Dream Career Co.,Ltd.,Tokyo,Japan","institution_ids":["https://openalex.org/I4210124472"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5111379084"],"corresponding_institution_ids":["https://openalex.org/I203021718"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.73804736,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"486","last_page":"490"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.5601000189781189,"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":0.5601000189781189,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.026599999517202377,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T12707","display_name":"Vehicle License Plate Recognition","score":0.01769999973475933,"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/traffic-sign","display_name":"Traffic sign","score":0.6007000207901001},{"id":"https://openalex.org/keywords/sign","display_name":"Sign (mathematics)","score":0.5799000263214111},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4641000032424927},{"id":"https://openalex.org/keywords/recall","display_name":"Recall","score":0.3411000072956085},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3357999920845032},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.32690000534057617}],"concepts":[{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6680999994277954},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6399999856948853},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.628600001335144},{"id":"https://openalex.org/C2983860417","wikidata":"https://www.wikidata.org/wiki/Q170285","display_name":"Traffic sign","level":3,"score":0.6007000207901001},{"id":"https://openalex.org/C139676723","wikidata":"https://www.wikidata.org/wiki/Q1193832","display_name":"Sign (mathematics)","level":2,"score":0.5799000263214111},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4641000032424927},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.3411000072956085},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3357999920845032},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.32690000534057617},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.32429999113082886},{"id":"https://openalex.org/C6528762","wikidata":"https://www.wikidata.org/wiki/Q1574298","display_name":"Traffic sign recognition","level":4,"score":0.2874999940395355},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2856999933719635},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.2793000042438507},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.27300000190734863},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2596000134944916}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icves65691.2025.11376052","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icves65691.2025.11376052","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W2039460612","https://openalex.org/W2912642076","https://openalex.org/W4228999275","https://openalex.org/W4399856254"],"related_works":[],"abstract_inverted_index":{"In":[0,53],"this":[1,105],"paper,":[2],"we":[3,56],"study":[4],"a":[5,19,37,40,44,74,96,140],"method":[6,38,128],"of":[7,14,26,61,98,139],"acquiring":[8,27],"sign":[9,28],"information":[10,29],"for":[11,50,125,131],"the":[12,58,80,84,92,99,116,121,126,132,137],"purpose":[13],"determining":[15],"safe":[16],"routes":[17],"in":[18,145],"bicycle":[20],"navigation":[21],"system.":[22],"The":[23,108],"proposed":[24,133],"methods":[25,101,114],"are":[30],"based":[31,67],"on":[32,68,71],"Google":[33],"Street":[34],"View":[35],"and":[36,95,129],"using":[39,83,104],"drive":[41,64,141],"recorder.":[42],"YOLOv8,":[43],"real-time":[45],"object":[46],"detector,":[47],"is":[48,123],"used":[49],"image":[51],"recognition.":[52],"preliminary":[54],"experiments,":[55],"evaluated":[57],"recognition":[59,81],"accuracy":[60,82],"signs":[62],"from":[63],"recorder":[65,142],"videos":[66,70],"driving":[69],"motorways.":[72],"As":[73],"result,":[75],"it":[76],"was":[77,91,102],"determined":[78],"that":[79,112,136],"YOLOv8":[85],"model":[86],"with":[87],"100":[88],"training":[89],"cycles":[90],"most":[93],"suitable,":[94],"comparison":[97,109],"two":[100],"conducted":[103],"weight":[106],"file.":[107],"results":[110,144],"showed":[111],"both":[113],"have":[115],"same":[117],"recall":[118],"(78%),":[119],"but":[120],"precision":[122],"41%":[124],"conventional":[127],"19%":[130],"method,":[134],"indicating":[135],"use":[138],"often":[143],"false":[146],"positives.":[147]},"counts_by_year":[],"updated_date":"2026-02-13T13:36:01.753593","created_date":"2026-02-12T00:00:00"}
