{"id":"https://openalex.org/W4280511929","doi":"https://doi.org/10.3390/s22103783","title":"Research on Deep Learning Automatic Vehicle Recognition Algorithm Based on RES-YOLO Model","display_name":"Research on Deep Learning Automatic Vehicle Recognition Algorithm Based on RES-YOLO Model","publication_year":2022,"publication_date":"2022-05-16","ids":{"openalex":"https://openalex.org/W4280511929","doi":"https://doi.org/10.3390/s22103783","pmid":"https://pubmed.ncbi.nlm.nih.gov/35632188"},"language":"en","primary_location":{"id":"doi:10.3390/s22103783","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22103783","pdf_url":"https://www.mdpi.com/1424-8220/22/10/3783/pdf?version=1652701240","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/1424-8220/22/10/3783/pdf?version=1652701240","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015976016","display_name":"Yanyi Li","orcid":"https://orcid.org/0000-0002-5529-868X"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanyi Li","raw_affiliation_strings":["College of Surveying and Geo-Informatics, Tongji Univesity, Shanghai 200092, China"],"raw_orcid":"https://orcid.org/0000-0002-5529-868X","affiliations":[{"raw_affiliation_string":"College of Surveying and Geo-Informatics, Tongji Univesity, Shanghai 200092, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101484170","display_name":"Jian Wang","orcid":"https://orcid.org/0000-0003-2504-3536"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jian Wang","raw_affiliation_strings":["College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China","institution_ids":["https://openalex.org/I80143920"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013784616","display_name":"Jin Huang","orcid":"https://orcid.org/0000-0003-1309-8329"},"institutions":[{"id":"https://openalex.org/I31847773","display_name":"Zhejiang Ocean University","ror":"https://ror.org/03mys6533","country_code":"CN","type":"education","lineage":["https://openalex.org/I31847773"]},{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin Huang","raw_affiliation_strings":["Ocean College, Zhejiang University, Zhoushan 316021, China"],"raw_orcid":"https://orcid.org/0000-0003-1309-8329","affiliations":[{"raw_affiliation_string":"Ocean College, Zhejiang University, Zhoushan 316021, China","institution_ids":["https://openalex.org/I31847773","https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057717494","display_name":"Yuping Li","orcid":"https://orcid.org/0000-0002-0188-4018"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuping Li","raw_affiliation_strings":["College of Surveying and Geo-Informatics, Tongji Univesity, Shanghai 200092, China"],"raw_orcid":"https://orcid.org/0000-0002-0188-4018","affiliations":[{"raw_affiliation_string":"College of Surveying and Geo-Informatics, Tongji Univesity, Shanghai 200092, China","institution_ids":["https://openalex.org/I116953780"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101484170"],"corresponding_institution_ids":["https://openalex.org/I80143920"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2673},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2673},"fwci":3.7252,"has_fulltext":true,"cited_by_count":49,"citation_normalized_percentile":{"value":0.94849731,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"22","issue":"10","first_page":"3783","last_page":"3783"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9984999895095825,"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":0.9984999895095825,"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":0.9805999994277954,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9674999713897705,"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":0.6632741689682007},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.5671402812004089},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.545362114906311},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5339383482933044},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5055277347564697},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.49326223134994507},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.44289085268974304},{"id":"https://openalex.org/keywords/sensitivity","display_name":"Sensitivity (control systems)","score":0.42579129338264465},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3969303369522095},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1605066955089569}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6632741689682007},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.5671402812004089},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.545362114906311},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5339383482933044},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5055277347564697},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.49326223134994507},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44289085268974304},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.42579129338264465},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3969303369522095},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1605066955089569},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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}],"mesh":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":5,"locations":[{"id":"doi:10.3390/s22103783","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22103783","pdf_url":"https://www.mdpi.com/1424-8220/22/10/3783/pdf?version=1652701240","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:35632188","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35632188","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:doaj.org/article:a5509efd65fa4e11bd69de7208658dc2","is_oa":true,"landing_page_url":"https://doaj.org/article/a5509efd65fa4e11bd69de7208658dc2","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 22, Iss 10, p 3783 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/22/10/3783/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s22103783","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"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; Volume 22; Issue 10; Pages: 3783","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:9143950","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9143950","pdf_url":null,"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"}],"best_oa_location":{"id":"doi:10.3390/s22103783","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22103783","pdf_url":"https://www.mdpi.com/1424-8220/22/10/3783/pdf?version=1652701240","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":[{"display_name":"Peace, Justice and strong institutions","score":0.49000000953674316,"id":"https://metadata.un.org/sdg/16"},{"display_name":"Reduced inequalities","score":0.44999998807907104,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320332814","display_name":"UC Berkeley College of Chemistry","ror":"https://ror.org/01an7q238"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4280511929.pdf","grobid_xml":"https://content.openalex.org/works/W4280511929.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W78383390","https://openalex.org/W639708223","https://openalex.org/W2036738900","https://openalex.org/W2104361640","https://openalex.org/W2109255472","https://openalex.org/W2124368862","https://openalex.org/W2139916508","https://openalex.org/W2151103935","https://openalex.org/W2169122647","https://openalex.org/W2172183560","https://openalex.org/W2193145675","https://openalex.org/W2238927032","https://openalex.org/W2536526744","https://openalex.org/W2587248218","https://openalex.org/W2783606813","https://openalex.org/W2783820472","https://openalex.org/W2901309398","https://openalex.org/W2912136793","https://openalex.org/W2912871542","https://openalex.org/W2963037989","https://openalex.org/W2972167550","https://openalex.org/W3009899240","https://openalex.org/W3106250896","https://openalex.org/W3106976972","https://openalex.org/W3110235765","https://openalex.org/W3122939190","https://openalex.org/W3127700311","https://openalex.org/W3138709608","https://openalex.org/W3188445554","https://openalex.org/W3201006331","https://openalex.org/W3207919513","https://openalex.org/W3207948380","https://openalex.org/W3214060228","https://openalex.org/W4205762292","https://openalex.org/W4242613020","https://openalex.org/W6683411478","https://openalex.org/W6792497077","https://openalex.org/W6802620288","https://openalex.org/W6823831963"],"related_works":["https://openalex.org/W4388321867","https://openalex.org/W2027108423","https://openalex.org/W1570939702","https://openalex.org/W1855666948","https://openalex.org/W2758561209","https://openalex.org/W1548095260","https://openalex.org/W2343361478","https://openalex.org/W2781711915","https://openalex.org/W2112817590","https://openalex.org/W1555291398"],"abstract_inverted_index":{"With":[0],"the":[1,47,66,76,80,105,127,146,155,179,187,204,209,218,246,253],"introduction":[2],"of":[3,69,79,150,168,229,255],"concepts":[4],"such":[5,30],"as":[6,31],"ubiquitous":[7],"mapping,":[8],"mapping-related":[9],"technologies":[10],"are":[11,21],"gradually":[12],"applied":[13],"in":[14,24,33,248],"autonomous":[15],"driving":[16],"and":[17,27,44,62,89,102,115,137,142,154,182,194,200,235],"target":[18,120,257],"recognition.":[19],"There":[20],"many":[22],"problems":[23,61],"vision":[25],"measurement":[26],"remote":[28],"sensing,":[29],"difficulty":[32],"automatic":[34,67],"vehicle":[35,42,70,110,134,232,256],"discrimination,":[36],"high":[37],"missing":[38,141],"rates":[39],"under":[40,160,240,259],"multiple":[41,133],"targets,":[43],"sensitivity":[45],"to":[46,58,65,152],"external":[48],"environment.":[49],"This":[50],"paper":[51,74,250],"proposes":[52],"an":[53],"improved":[54],"RES-YOLO":[55,188],"detection":[56,68,77,111,258],"algorithm":[57,83,129,170,189],"solve":[59],"these":[60],"applies":[63],"it":[64],"targets.":[71],"Specifically,":[72],"this":[73,249],"improves":[75],"effect":[78],"traditional":[81],"YOLO":[82,107],"by":[84,214],"selecting":[85],"optimized":[86,106],"feature":[87],"networks":[88],"constructing":[90],"adaptive":[91],"loss":[92],"functions.":[93],"The":[94,165,221],"BDD100K":[95],"data":[96,162,192,196,233],"set":[97],"was":[98],"used":[99],"for":[100,190],"training":[101,210],"verification.":[103],"Additionally,":[104],"deep":[108],"learning":[109],"model":[112],"is":[113,171,198,212,223],"obtained":[114],"compared":[116,216],"with":[117,145,217,226],"recent":[118],"advanced":[119],"recognition":[121,238],"algorithms.":[122],"Experimental":[123],"results":[124],"show":[125],"that":[126],"proposed":[128],"can":[130,138,251],"automatically":[131],"identify":[132],"targets":[135],"effectively":[136],"significantly":[139],"reduce":[140],"false":[143],"rates,":[144],"local":[147,230],"optimal":[148],"accuracy":[149,157,167,239],"up":[151],"95%":[153],"average":[156,166,185],"above":[158],"86%":[159],"large":[161,195],"volume":[163,193,197],"detection.":[164],"our":[169],"higher":[172,202],"than":[173,203],"all":[174],"five":[175,227],"other":[176],"algorithms":[177],"including":[178],"latest":[180],"SSD":[181],"Faster-RCNN.":[183],"In":[184,207,244],"accuracy,":[186],"small":[191],"1.0%":[199],"1.7%":[201],"original":[205,219],"YOLO.":[206],"addition,":[208],"time":[211],"shortened":[213],"7.3%":[215],"algorithm.":[220],"network":[222],"then":[224],"tested":[225],"types":[228],"measured":[231],"sets":[234],"shows":[236],"satisfactory":[237],"different":[241,260],"interference":[242],"backgrounds.":[243],"short,":[245],"method":[247],"complete":[252],"task":[254],"environmental":[261],"interferences.":[262]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":18},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}