{"id":"https://openalex.org/W4313148257","doi":"https://doi.org/10.1109/icspcc55723.2022.9984614","title":"Detection of Dangerous Driving Behavior Based on CG-YOLOv5","display_name":"Detection of Dangerous Driving Behavior Based on CG-YOLOv5","publication_year":2022,"publication_date":"2022-10-25","ids":{"openalex":"https://openalex.org/W4313148257","doi":"https://doi.org/10.1109/icspcc55723.2022.9984614"},"language":"en","primary_location":{"id":"doi:10.1109/icspcc55723.2022.9984614","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icspcc55723.2022.9984614","pdf_url":null,"source":{"id":"https://openalex.org/S4363608295","display_name":"2022 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)","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 Signal Processing, Communications and Computing (ICSPCC)","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/A5100381054","display_name":"Weiguo Zhang","orcid":"https://orcid.org/0000-0002-8393-3185"},"institutions":[{"id":"https://openalex.org/I110440473","display_name":"Xi'an University of Science and Technology","ror":"https://ror.org/046fkpt18","country_code":"CN","type":"education","lineage":["https://openalex.org/I110440473"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weiguo Zhang","raw_affiliation_strings":["Xi’an University of Science and Technology,College of Computer Science and Technology,Xi’an,China"],"affiliations":[{"raw_affiliation_string":"Xi’an University of Science and Technology,College of Computer Science and Technology,Xi’an,China","institution_ids":["https://openalex.org/I110440473"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008259611","display_name":"Yunxia Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I110440473","display_name":"Xi'an University of Science and Technology","ror":"https://ror.org/046fkpt18","country_code":"CN","type":"education","lineage":["https://openalex.org/I110440473"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunxia Xiao","raw_affiliation_strings":["Xi’an University of Science and Technology,College of Computer Science and Technology,Xi’an,China"],"affiliations":[{"raw_affiliation_string":"Xi’an University of Science and Technology,College of Computer Science and Technology,Xi’an,China","institution_ids":["https://openalex.org/I110440473"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100381054"],"corresponding_institution_ids":["https://openalex.org/I110440473"],"apc_list":null,"apc_paid":null,"fwci":0.1199,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.45315842,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"34","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9983000159263611,"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":0.9983000159263611,"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":0.9904999732971191,"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":0.9697999954223633,"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":0.7651003003120422},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.734890341758728},{"id":"https://openalex.org/keywords/interference","display_name":"Interference (communication)","score":0.6578323841094971},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5958666801452637},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5867272615432739},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5633584856987},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4927501976490021},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4772986173629761},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45701247453689575},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4513328969478607},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3674079179763794},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.13893729448318481},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.12263727188110352},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.10531198978424072}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7651003003120422},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.734890341758728},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.6578323841094971},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5958666801452637},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5867272615432739},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5633584856987},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4927501976490021},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4772986173629761},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45701247453689575},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4513328969478607},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3674079179763794},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.13893729448318481},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.12263727188110352},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.10531198978424072},{"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icspcc55723.2022.9984614","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icspcc55723.2022.9984614","pdf_url":null,"source":{"id":"https://openalex.org/S4363608295","display_name":"2022 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)","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 Signal Processing, Communications and Computing (ICSPCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.7599999904632568,"display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2109255472","https://openalex.org/W2109682111","https://openalex.org/W2144506857","https://openalex.org/W2193145675","https://openalex.org/W2884585870","https://openalex.org/W2982083293","https://openalex.org/W2997747012","https://openalex.org/W3035414587","https://openalex.org/W3042011474","https://openalex.org/W3106250896","https://openalex.org/W3210552291","https://openalex.org/W6637373629","https://openalex.org/W6777046832"],"related_works":["https://openalex.org/W2372403409","https://openalex.org/W2375786911","https://openalex.org/W4242726756","https://openalex.org/W2367630196","https://openalex.org/W4387838477","https://openalex.org/W3147584709","https://openalex.org/W756944427","https://openalex.org/W2977677679","https://openalex.org/W2061571973","https://openalex.org/W3088721469"],"abstract_inverted_index":{"In":[0,26],"order":[1],"to":[2,19,63,82,99,153],"avoid":[3],"huge":[4],"traffic":[5],"accidents":[6],"caused":[7],"by":[8],"dangerous":[9,159],"driving":[10,160],"behavior":[11,22,161],"on":[12],"the":[13,29,33,37,40,52,61,65,71,75,84,87,101,104,112,121,125,135,138,144,154,165],"way,":[14],"it":[15],"is":[16,49,58,92,118,129,140],"very":[17],"important":[18],"detect":[20],"this":[21,116],"in":[23,60,74,164],"real":[24,166],"time.":[25],"view":[27],"of":[28,32,39,77,86,95,103,115,158,162],"high":[30],"loss":[31,85],"existing":[34],"methods":[35],"and":[36,69,120,148],"interference":[38,73],"data":[41,128],"set":[42],"background,":[43],"an":[44],"improved":[45],"YOLOv5":[46],"detection":[47,105],"method":[48,117],"proposed.":[50],"Firstly,":[51],"convolution":[53,91,97],"block":[54],"attention":[55],"module":[56],"mechanism":[57],"integrated":[59],"network":[62,146],"enhance":[64],"feature":[66,78],"expression":[67],"ability":[68],"suppress":[70],"background":[72],"process":[76],"fusion,":[79],"so":[80],"as":[81,130,132],"reduce":[83],"algorithm.":[88],"Secondly,":[89],"Ghost":[90],"used":[93],"instead":[94],"ordinary":[96],"operation":[98],"realize":[100],"lightweight":[102],"model.":[106],"The":[107],"experimental":[108],"results":[109],"show":[110],"that":[111],"recognition":[113],"accuracy":[114],"99.9%,":[119],"reasoning":[122],"time":[123],"under":[124],"same":[126,136],"test":[127],"low":[131],"3.895s.":[133],"At":[134],"time,":[137],"model":[139],"much":[141],"smaller":[142],"than":[143],"original":[145],"model,":[147],"can":[149],"be":[150],"effectively":[151],"applied":[152],"real-time":[155],"accurate":[156],"monitoring":[157],"drivers":[163],"environment.":[167]},"counts_by_year":[{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}