{"id":"https://openalex.org/W4294069594","doi":"https://doi.org/10.1109/icce-taiwan55306.2022.9869222","title":"Data Augmentation Method for Improving Vehicle Detection and Recognition Performance","display_name":"Data Augmentation Method for Improving Vehicle Detection and Recognition Performance","publication_year":2022,"publication_date":"2022-07-06","ids":{"openalex":"https://openalex.org/W4294069594","doi":"https://doi.org/10.1109/icce-taiwan55306.2022.9869222"},"language":"en","primary_location":{"id":"doi:10.1109/icce-taiwan55306.2022.9869222","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce-taiwan55306.2022.9869222","pdf_url":null,"source":{"id":"https://openalex.org/S4363607852","display_name":"2022 IEEE International Conference on Consumer Electronics - Taiwan","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Consumer Electronics - Taiwan","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/A5053133694","display_name":"Xiu-Zhi Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I118292597","display_name":"National Taipei University of Technology","ror":"https://ror.org/00cn92c09","country_code":"TW","type":"education","lineage":["https://openalex.org/I118292597"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Xiu-Zhi Chen","raw_affiliation_strings":["National Taipei University of Technology,Dept. Computer Science and Information Engineering,Taipei,Taiwan","Dept. Computer Science and Information Engineering, National Taipei University of Technology, Taipei, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taipei University of Technology,Dept. Computer Science and Information Engineering,Taipei,Taiwan","institution_ids":["https://openalex.org/I118292597"]},{"raw_affiliation_string":"Dept. Computer Science and Information Engineering, National Taipei University of Technology, Taipei, Taiwan","institution_ids":["https://openalex.org/I118292597"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003666599","display_name":"Chen-Pu Cheng","orcid":null},"institutions":[{"id":"https://openalex.org/I118292597","display_name":"National Taipei University of Technology","ror":"https://ror.org/00cn92c09","country_code":"TW","type":"education","lineage":["https://openalex.org/I118292597"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chen-Pu Cheng","raw_affiliation_strings":["National Taipei University of Technology,Dept. Computer Science and Information Engineering,Taipei,Taiwan","Dept. Computer Science and Information Engineering, National Taipei University of Technology, Taipei, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taipei University of Technology,Dept. Computer Science and Information Engineering,Taipei,Taiwan","institution_ids":["https://openalex.org/I118292597"]},{"raw_affiliation_string":"Dept. Computer Science and Information Engineering, National Taipei University of Technology, Taipei, Taiwan","institution_ids":["https://openalex.org/I118292597"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100670010","display_name":"Yen\u2010Lin Chen","orcid":"https://orcid.org/0000-0001-7717-9393"},"institutions":[{"id":"https://openalex.org/I118292597","display_name":"National Taipei University of Technology","ror":"https://ror.org/00cn92c09","country_code":"TW","type":"education","lineage":["https://openalex.org/I118292597"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yen-Lin Chen","raw_affiliation_strings":["National Taipei University of Technology,Dept. Computer Science and Information Engineering,Taipei,Taiwan","Dept. Computer Science and Information Engineering, National Taipei University of Technology, Taipei, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taipei University of Technology,Dept. Computer Science and Information Engineering,Taipei,Taiwan","institution_ids":["https://openalex.org/I118292597"]},{"raw_affiliation_string":"Dept. Computer Science and Information Engineering, National Taipei University of Technology, Taipei, Taiwan","institution_ids":["https://openalex.org/I118292597"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I118292597"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"419","last_page":"420"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9987999796867371,"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":0.9987999796867371,"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":0.9858999848365784,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9797999858856201,"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":0.8103565573692322},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.6524354219436646},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6026226282119751},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5502800345420837},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.530942440032959},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.51261967420578},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4870660603046417},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41552963852882385},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3948490619659424},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.11875545978546143}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8103565573692322},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.6524354219436646},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6026226282119751},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5502800345420837},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.530942440032959},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.51261967420578},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4870660603046417},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41552963852882385},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3948490619659424},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.11875545978546143},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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":1,"locations":[{"id":"doi:10.1109/icce-taiwan55306.2022.9869222","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce-taiwan55306.2022.9869222","pdf_url":null,"source":{"id":"https://openalex.org/S4363607852","display_name":"2022 IEEE International Conference on Consumer Electronics - Taiwan","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Consumer Electronics - Taiwan","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":9,"referenced_works":["https://openalex.org/W2955639361","https://openalex.org/W2989111758","https://openalex.org/W2993182889","https://openalex.org/W3018757597","https://openalex.org/W3034528136","https://openalex.org/W3081167590","https://openalex.org/W3092371156","https://openalex.org/W4206621318","https://openalex.org/W4214520160"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4224009465","https://openalex.org/W4306674287","https://openalex.org/W4286629047","https://openalex.org/W4205958290","https://openalex.org/W4384212932","https://openalex.org/W4390590544","https://openalex.org/W2096195258","https://openalex.org/W4285322112","https://openalex.org/W4292794239"],"abstract_inverted_index":{"Vehicle":[0],"detection":[1,58],"and":[2,34,59],"recognition":[3,60],"are":[4,14],"now":[5],"implemented":[6],"through":[7],"powerful":[8],"machine":[9],"learning":[10,20],"methods,":[11],"those":[12],"methods":[13],"not":[15],"only":[16],"relying":[17],"on":[18,81],"clever":[19],"strategies,":[21],"but":[22],"also":[23],"require":[24],"high":[25,30,53],"quality":[26,31,54],"datasets.":[27],"To":[28],"obtain":[29],"datasets,":[32],"time-consuming":[33],"grueling":[35],"processing":[36],"is":[37,49],"needed.":[38],"In":[39],"this":[40],"research,":[41],"we":[42],"proposed":[43,71],"a":[44,63],"data":[45,72,84,111],"augmentation":[46,73],"concept":[47,74],"that":[48,93],"able":[50],"to":[51,103],"prepare":[52],"datasets":[55],"for":[56],"vehicle":[57],"training":[61,83],"in":[62],"more":[64],"efficient":[65],"approach.":[66],"The":[67,90],"effectiveness":[68],"of":[69,87],"our":[70],"has":[75],"been":[76],"proved":[77],"by":[78],"applying":[79],"it":[80],"the":[82,94,104],"preparing":[85],"process":[86],"YOLOv4":[88,105],"model.":[89],"result":[91],"shows":[92],"mean":[95],"average":[96],"precision":[97],"(mAP)":[98],"had":[99],"increased":[100],"1.93%":[101],"comparing":[102],"model":[106],"which":[107],"was":[108],"trained":[109],"without":[110],"augmentation.":[112]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
