{"id":"https://openalex.org/W4372341724","doi":"https://doi.org/10.1109/icassp49357.2023.10096629","title":"YOLOX-B: A Better Yolox Model for Real-Time Driver Behavior Detection","display_name":"YOLOX-B: A Better Yolox Model for Real-Time Driver Behavior Detection","publication_year":2023,"publication_date":"2023-05-05","ids":{"openalex":"https://openalex.org/W4372341724","doi":"https://doi.org/10.1109/icassp49357.2023.10096629"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49357.2023.10096629","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49357.2023.10096629","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5102956835","display_name":"Xu Guo","orcid":"https://orcid.org/0000-0002-6072-5893"},"institutions":[{"id":"https://openalex.org/I2722730","display_name":"Inner Mongolia University","ror":"https://ror.org/0106qb496","country_code":"CN","type":"education","lineage":["https://openalex.org/I2722730"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Guo","raw_affiliation_strings":["Inner Mongolia University,Hohhot,China","Inner Mongolia University, Hohhot, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Inner Mongolia University,Hohhot,China","institution_ids":["https://openalex.org/I2722730"]},{"raw_affiliation_string":"Inner Mongolia University, Hohhot, China","institution_ids":["https://openalex.org/I2722730"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014222203","display_name":"Ming Ma","orcid":"https://orcid.org/0009-0005-7119-6332"},"institutions":[{"id":"https://openalex.org/I2722730","display_name":"Inner Mongolia University","ror":"https://ror.org/0106qb496","country_code":"CN","type":"education","lineage":["https://openalex.org/I2722730"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Ma","raw_affiliation_strings":["Inner Mongolia University,Hohhot,China","Inner Mongolia University, Hohhot, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Inner Mongolia University,Hohhot,China","institution_ids":["https://openalex.org/I2722730"]},{"raw_affiliation_string":"Inner Mongolia University, Hohhot, China","institution_ids":["https://openalex.org/I2722730"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100605309","display_name":"Jiaqiang Zhang","orcid":"https://orcid.org/0000-0002-0174-6803"},"institutions":[{"id":"https://openalex.org/I2722730","display_name":"Inner Mongolia University","ror":"https://ror.org/0106qb496","country_code":"CN","type":"education","lineage":["https://openalex.org/I2722730"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaqiang Zhang","raw_affiliation_strings":["Inner Mongolia University,Hohhot,China","Inner Mongolia University, Hohhot, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Inner Mongolia University,Hohhot,China","institution_ids":["https://openalex.org/I2722730"]},{"raw_affiliation_string":"Inner Mongolia University, Hohhot, China","institution_ids":["https://openalex.org/I2722730"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100345011","display_name":"Shaojie Li","orcid":"https://orcid.org/0000-0002-7203-2488"},"institutions":[{"id":"https://openalex.org/I2722730","display_name":"Inner Mongolia University","ror":"https://ror.org/0106qb496","country_code":"CN","type":"education","lineage":["https://openalex.org/I2722730"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaojie Li","raw_affiliation_strings":["Inner Mongolia University,Hohhot,China","Inner Mongolia University, Hohhot, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Inner Mongolia University,Hohhot,China","institution_ids":["https://openalex.org/I2722730"]},{"raw_affiliation_string":"Inner Mongolia University, Hohhot, China","institution_ids":["https://openalex.org/I2722730"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I2722730"],"apc_list":null,"apc_paid":null,"fwci":0.6069,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.75329373,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.998199999332428,"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":0.9904000163078308,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7324128150939941},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.705407440662384},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6084543466567993},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6068288683891296},{"id":"https://openalex.org/keywords/pascal","display_name":"Pascal (unit)","score":0.5534574389457703},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5199679136276245},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.48301801085472107},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4749997854232788},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43716496229171753},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.43449339270591736},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4319155216217041},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.40362975001335144},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1671701967716217},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.08299189805984497}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7324128150939941},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.705407440662384},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6084543466567993},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6068288683891296},{"id":"https://openalex.org/C75608658","wikidata":"https://www.wikidata.org/wiki/Q44395","display_name":"Pascal (unit)","level":2,"score":0.5534574389457703},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5199679136276245},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.48301801085472107},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4749997854232788},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43716496229171753},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.43449339270591736},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4319155216217041},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.40362975001335144},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1671701967716217},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.08299189805984497},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49357.2023.10096629","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49357.2023.10096629","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321408","display_name":"Ministry of Education","ror":"https://ror.org/01p262204"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1923697677","https://openalex.org/W2027286771","https://openalex.org/W2109255472","https://openalex.org/W2412782625","https://openalex.org/W2570343428","https://openalex.org/W2592939477","https://openalex.org/W2630837129","https://openalex.org/W2916809146","https://openalex.org/W2963037989","https://openalex.org/W2987322772","https://openalex.org/W3018757597","https://openalex.org/W3096609285","https://openalex.org/W3106250896","https://openalex.org/W3147532979","https://openalex.org/W3184439416","https://openalex.org/W3208826636","https://openalex.org/W4214627427","https://openalex.org/W4289822292","https://openalex.org/W4293584584","https://openalex.org/W4386076325","https://openalex.org/W6640295612","https://openalex.org/W6715287400","https://openalex.org/W6739696289","https://openalex.org/W6750227808","https://openalex.org/W6777046832","https://openalex.org/W6778485988","https://openalex.org/W6785652829","https://openalex.org/W6795488267","https://openalex.org/W6798838024","https://openalex.org/W6803118227","https://openalex.org/W6849520326"],"related_works":["https://openalex.org/W2022849497","https://openalex.org/W2407190427","https://openalex.org/W3081299480","https://openalex.org/W2919210741","https://openalex.org/W2907584218","https://openalex.org/W3002446410","https://openalex.org/W3177249605","https://openalex.org/W4390224712","https://openalex.org/W4376620596","https://openalex.org/W4322096758"],"abstract_inverted_index":{"In":[0],"the":[1,5,11,18,57,66,85,89,102,112,120,127,130],"coal":[2],"transportation":[3],"scene,":[4],"object":[6],"detection":[7,14,25,103],"model":[8,33,90],"proposed":[9],"for":[10],"driver":[12,122],"behavior":[13,123],"task":[15],"generally":[16],"has":[17],"problems":[19],"of":[20,26,48,59,68,105],"inaccurate":[21],"positioning":[22],"and":[23,64,100,119,136,145],"difficult":[24],"small":[27,106],"objects,":[28],"we":[29],"propose":[30],"a":[31,37,74,97],"new":[32],"YOLOX-B,":[34],"which":[35],"introduces":[36],"serialized":[38,53],"atrous":[39,54,69],"spatial":[40],"pyramid":[41],"pooling":[42],"structure":[43],"(S-ASPP),":[44],"obtains":[45],"different":[46],"sizes":[47],"receptive":[49],"field":[50],"information":[51,60],"through":[52],"convolution,":[55,82],"solves":[56],"problem":[58],"loss":[61],"in":[62,96],"max-pooling,":[63],"maximizes":[65],"efficiency":[67],"convolution.":[70],"Meanwhile,":[71],"by":[72,143],"introducing":[73],"lightweight":[75],"feature":[76],"reorganization":[77],"module":[78],"based":[79],"on":[80,111],"transposed":[81],"adaptively":[83],"predicting":[84],"up-sampling":[86],"kernel":[87],"weight,":[88],"can":[91],"better":[92],"complete":[93],"pixel":[94],"recovery":[95],"weighted":[98],"way":[99],"improve":[101],"accuracy":[104],"objects.":[107],"The":[108],"experimental":[109],"results":[110],"publicly":[113],"available":[114],"PASCAL":[115],"VOC":[116],"2012":[117],"dataset":[118,124],"self-built":[121],"demonstrate":[125],"that":[126],"YOLOX-B":[128],"maintains":[129],"same":[131],"inference":[132],"speed":[133],"as":[134],"YOLOX-S,":[135],"its":[137],"mean":[138],"Average":[139],"Precisions(mAPs)":[140],"are":[141],"improved":[142],"4.4%":[144],"0.8%,":[146],"respectively.":[147]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
