{"id":"https://openalex.org/W4390066329","doi":"https://doi.org/10.1145/3635175.3635187","title":"The Research on Traffic Flow Statistics Based on YOLOv5 and Attention Mechanism","display_name":"The Research on Traffic Flow Statistics Based on YOLOv5 and Attention Mechanism","publication_year":2023,"publication_date":"2023-11-21","ids":{"openalex":"https://openalex.org/W4390066329","doi":"https://doi.org/10.1145/3635175.3635187"},"language":"en","primary_location":{"id":"doi:10.1145/3635175.3635187","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3635175.3635187","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3635175.3635187","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 8th International Conference on Intelligent Information Processing","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3635175.3635187","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072946676","display_name":"Y. Yu","orcid":"https://orcid.org/0009-0000-7946-4753"},"institutions":[{"id":"https://openalex.org/I25399270","display_name":"Southwest Forestry University","ror":"https://ror.org/03dfa9f06","country_code":"CN","type":"education","lineage":["https://openalex.org/I25399270"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiwang Yu","raw_affiliation_strings":["Southwest Forestry University, China"],"raw_orcid":"https://orcid.org/0009-0000-7946-4753","affiliations":[{"raw_affiliation_string":"Southwest Forestry University, China","institution_ids":["https://openalex.org/I25399270"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101955858","display_name":"Yongke Sun","orcid":"https://orcid.org/0000-0003-3989-5502"},"institutions":[{"id":"https://openalex.org/I25399270","display_name":"Southwest Forestry University","ror":"https://ror.org/03dfa9f06","country_code":"CN","type":"education","lineage":["https://openalex.org/I25399270"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongke Sun","raw_affiliation_strings":["Southwest Forestry University, China"],"raw_orcid":"https://orcid.org/0000-0003-3989-5502","affiliations":[{"raw_affiliation_string":"Southwest Forestry University, China","institution_ids":["https://openalex.org/I25399270"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050922665","display_name":"Yong Cao","orcid":"https://orcid.org/0000-0002-4138-187X"},"institutions":[{"id":"https://openalex.org/I25399270","display_name":"Southwest Forestry University","ror":"https://ror.org/03dfa9f06","country_code":"CN","type":"education","lineage":["https://openalex.org/I25399270"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Cao","raw_affiliation_strings":["Southwest Forestry University, China"],"raw_orcid":"https://orcid.org/0000-0002-4138-187X","affiliations":[{"raw_affiliation_string":"Southwest Forestry University, China","institution_ids":["https://openalex.org/I25399270"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I25399270"],"apc_list":null,"apc_paid":null,"fwci":0.1212,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.47350635,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"57","last_page":"61"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9983999729156494,"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":0.9983999729156494,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9865999817848206,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/computer-science","display_name":"Computer science","score":0.7477031946182251},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.6232452392578125},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.6192819476127625},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5397094488143921},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.5072864890098572},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49645859003067017},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.4730246067047119},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4436686933040619},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44362515211105347},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4433088004589081},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3660615384578705},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3310912251472473},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.12366536259651184},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1200534999370575},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10345837473869324},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.10128012299537659}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7477031946182251},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.6232452392578125},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.6192819476127625},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5397094488143921},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.5072864890098572},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49645859003067017},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.4730246067047119},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4436686933040619},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44362515211105347},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4433088004589081},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3660615384578705},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3310912251472473},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.12366536259651184},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1200534999370575},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10345837473869324},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.10128012299537659},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3635175.3635187","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3635175.3635187","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3635175.3635187","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 8th International Conference on Intelligent Information Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3635175.3635187","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3635175.3635187","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3635175.3635187","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 8th International Conference on Intelligent Information Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.4099999964237213,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4390066329.pdf","grobid_xml":"https://content.openalex.org/works/W4390066329.grobid-xml"},"referenced_works_count":17,"referenced_works":["https://openalex.org/W2579318141","https://openalex.org/W3096450052","https://openalex.org/W3099651116","https://openalex.org/W3111248667","https://openalex.org/W3129744991","https://openalex.org/W3158114921","https://openalex.org/W3158949235","https://openalex.org/W3166999786","https://openalex.org/W3190695173","https://openalex.org/W3202087911","https://openalex.org/W3214829036","https://openalex.org/W4212965978","https://openalex.org/W4221022253","https://openalex.org/W4231109964","https://openalex.org/W4281383072","https://openalex.org/W4315815571","https://openalex.org/W4378980239"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2055243143","https://openalex.org/W2611989081","https://openalex.org/W4230611425","https://openalex.org/W2731899572","https://openalex.org/W4304166257","https://openalex.org/W4294635752","https://openalex.org/W4383066092","https://openalex.org/W3215138031","https://openalex.org/W4321636575"],"abstract_inverted_index":{"Traffic":[0],"flow":[1,23,59],"statistics":[2,24],"technology":[3,8,25],"is":[4,118,136],"a":[5,32,38,64,79],"very":[6],"important":[7,17],"in":[9,62,78,83],"Intelligent":[10],"Transportation":[11],"Systems":[12],"(ITS),":[13],"and":[14,50,122,138],"plays":[15],"an":[16],"role.":[18],"In":[19],"recent":[20],"years,":[21],"traffic":[22,58],"based":[26,73],"on":[27,74,104],"deep":[28],"learning":[29],"has":[30,44],"become":[31],"new":[33],"research":[34],"direction.":[35],"YOLOv5,":[36,99],"as":[37],"single":[39],"stage":[40],"target":[41],"detection":[42],"algorithm,":[43],"the":[45,92,102,105],"advantage":[46],"of":[47,67,81],"fast":[48],"speed":[49],"high":[51],"accuracy":[52],"YOLOv5":[53,63],"can":[54],"be":[55],"applied":[56],"to":[57,111],"statistics.":[60],"However,":[61],"large":[65],"number":[66],"feature":[68],"concatenations":[69],"were":[70],"not":[71,124],"weighted":[72],"their":[75],"importance,":[76],"resulting":[77],"lack":[80],"focus":[82],"learning.":[84],"To":[85],"address":[86],"this":[87,89],"issue,":[88],"paper":[90],"introduces":[91],"CA":[93],"(coordinate":[94],"attention)":[95],"attention":[96,113],"mechanism":[97],"into":[98],"which":[100],"increases":[101],"mAP0.5:0.95":[103],"BIT-Vehicle":[106],"Dataset":[107],"by":[108],"1.4%.":[109],"Compared":[110],"other":[112],"mechanisms":[114],"our":[115,133],"proposed":[116],"method":[117,135],"better":[119],"than":[120],"them":[121],"does":[123],"affect":[125],"inference":[126],"speed.":[127],"The":[128],"experimental":[129],"results":[130],"demonstrate":[131],"that":[132],"fusion":[134],"feasible":[137],"effective.":[139]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-31T08:31:51.225901","created_date":"2025-10-10T00:00:00"}
