{"id":"https://openalex.org/W7158595588","doi":"https://doi.org/10.1109/access.2026.3687749","title":"ORAF-YOLO: A Lightweight Factory Unsafe Behavior Recognition Method With Occlusion-Robust Adaptive Fusion","display_name":"ORAF-YOLO: A Lightweight Factory Unsafe Behavior Recognition Method With Occlusion-Robust Adaptive Fusion","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7158595588","doi":"https://doi.org/10.1109/access.2026.3687749"},"language":"en","primary_location":{"id":"doi:10.1109/access.2026.3687749","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3687749","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2026.3687749","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054537903","display_name":"Ying Qin","orcid":"https://orcid.org/0000-0001-9131-5830"},"institutions":[{"id":"https://openalex.org/I2800556661","display_name":"China Tobacco","ror":"https://ror.org/030d08e08","country_code":"CN","type":"government","lineage":["https://openalex.org/I2800556661"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ying Qin","raw_affiliation_strings":["Hebei Baisha Tobacco Company Ltd., Baoding Cigarette Factory, Baoding, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hebei Baisha Tobacco Company Ltd., Baoding Cigarette Factory, Baoding, China","institution_ids":["https://openalex.org/I2800556661"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100437883","display_name":"Yuanyuan Chen","orcid":"https://orcid.org/0000-0003-0687-1643"},"institutions":[{"id":"https://openalex.org/I2800556661","display_name":"China Tobacco","ror":"https://ror.org/030d08e08","country_code":"CN","type":"government","lineage":["https://openalex.org/I2800556661"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanyuan Chen","raw_affiliation_strings":["Hebei Baisha Tobacco Company Ltd., Baoding Cigarette Factory, Baoding, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hebei Baisha Tobacco Company Ltd., Baoding Cigarette Factory, Baoding, China","institution_ids":["https://openalex.org/I2800556661"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134878764","display_name":"Yameng Tong","orcid":null},"institutions":[{"id":"https://openalex.org/I2800556661","display_name":"China Tobacco","ror":"https://ror.org/030d08e08","country_code":"CN","type":"government","lineage":["https://openalex.org/I2800556661"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yameng Tong","raw_affiliation_strings":["China Tobacco Hebei Industrial Company Ltd., Shijiazhuang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Tobacco Hebei Industrial Company Ltd., Shijiazhuang, China","institution_ids":["https://openalex.org/I2800556661"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109750560","display_name":"Tongshan Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I2800556661","display_name":"China Tobacco","ror":"https://ror.org/030d08e08","country_code":"CN","type":"government","lineage":["https://openalex.org/I2800556661"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tongshan Liu","raw_affiliation_strings":["Hebei Baisha Tobacco Company Ltd., Baoding Cigarette Factory, Baoding, China"],"raw_orcid":"https://orcid.org/0009-0002-3471-8291","affiliations":[{"raw_affiliation_string":"Hebei Baisha Tobacco Company Ltd., Baoding Cigarette Factory, Baoding, China","institution_ids":["https://openalex.org/I2800556661"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000052945","display_name":"Hao Cao","orcid":"https://orcid.org/0000-0002-4452-3853"},"institutions":[{"id":"https://openalex.org/I2800556661","display_name":"China Tobacco","ror":"https://ror.org/030d08e08","country_code":"CN","type":"government","lineage":["https://openalex.org/I2800556661"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Cao","raw_affiliation_strings":["Hebei Baisha Tobacco Company Ltd., Baoding Cigarette Factory, Baoding, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hebei Baisha Tobacco Company Ltd., Baoding Cigarette Factory, Baoding, China","institution_ids":["https://openalex.org/I2800556661"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103138049","display_name":"Fuqiang Wu","orcid":"https://orcid.org/0009-0005-1279-4164"},"institutions":[{"id":"https://openalex.org/I2800556661","display_name":"China Tobacco","ror":"https://ror.org/030d08e08","country_code":"CN","type":"government","lineage":["https://openalex.org/I2800556661"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fuqiang Wu","raw_affiliation_strings":["Hebei Baisha Tobacco Company Ltd., Baoding Cigarette Factory, Baoding, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hebei Baisha Tobacco Company Ltd., Baoding Cigarette Factory, Baoding, China","institution_ids":["https://openalex.org/I2800556661"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134894760","display_name":"Rui Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I2800556661","display_name":"China Tobacco","ror":"https://ror.org/030d08e08","country_code":"CN","type":"government","lineage":["https://openalex.org/I2800556661"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Shi","raw_affiliation_strings":["Hebei Baisha Tobacco Company Ltd., Baoding Cigarette Factory, Baoding, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hebei Baisha Tobacco Company Ltd., Baoding Cigarette Factory, Baoding, China","institution_ids":["https://openalex.org/I2800556661"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134889440","display_name":"Guowei Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I2800556661","display_name":"China Tobacco","ror":"https://ror.org/030d08e08","country_code":"CN","type":"government","lineage":["https://openalex.org/I2800556661"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guowei Zhang","raw_affiliation_strings":["Hebei Baisha Tobacco Company Ltd., Baoding Cigarette Factory, Baoding, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hebei Baisha Tobacco Company Ltd., Baoding Cigarette Factory, Baoding, China","institution_ids":["https://openalex.org/I2800556661"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124607983","display_name":"Yuling HE","orcid":null},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuling He","raw_affiliation_strings":["Hebei Key Laboratory of Electric Machinery Health Maintenance and Failure Prevention, North China Electric Power University, Baoding, China"],"raw_orcid":"https://orcid.org/0000-0003-2719-8128","affiliations":[{"raw_affiliation_string":"Hebei Key Laboratory of Electric Machinery Health Maintenance and Failure Prevention, North China Electric Power University, Baoding, China","institution_ids":["https://openalex.org/I153473198"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5054537903"],"corresponding_institution_ids":["https://openalex.org/I2800556661"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":26.8622,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.99425823,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"14","issue":null,"first_page":"69268","last_page":"69283"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.4275999963283539,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.4275999963283539,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.11760000139474869,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10667","display_name":"Emotion and Mood Recognition","score":0.032099999487400055,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/factory","display_name":"Factory (object-oriented programming)","score":0.7258999943733215},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5138999819755554},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.44920000433921814},{"id":"https://openalex.org/keywords/production","display_name":"Production (economics)","score":0.2824000120162964}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7440000176429749},{"id":"https://openalex.org/C40149104","wikidata":"https://www.wikidata.org/wiki/Q5620977","display_name":"Factory (object-oriented programming)","level":2,"score":0.7258999943733215},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5138999819755554},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.44920000433921814},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.33559998869895935},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3237999975681305},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2897000014781952},{"id":"https://openalex.org/C2778348673","wikidata":"https://www.wikidata.org/wiki/Q739302","display_name":"Production (economics)","level":2,"score":0.2824000120162964},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.26420000195503235},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.24879999458789825}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2026.3687749","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3687749","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:49bcc348c78a42129a96f33c2e4be886","is_oa":true,"landing_page_url":"https://doaj.org/article/49bcc348c78a42129a96f33c2e4be886","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":"IEEE Access, Vol 14, Pp 69268-69283 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3687749","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3687749","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Unsafe-behavior":[0],"recognition":[1,34],"in":[2,156],"factory":[3],"production":[4],"lines":[5],"remains":[6],"challenging":[7],"because":[8],"complex":[9,109,157],"backgrounds,":[10],"frequent":[11],"occlusion,":[12,54],"and":[13,21,75,97,128,153],"strict":[14],"real-time":[15,137],"requirements":[16],"often":[17],"degrade":[18],"detection":[19,150],"accuracy":[20],"robustness.":[22],"To":[23],"address":[24],"these":[25],"issues,":[26],"this":[27],"paper":[28],"proposes":[29],"ORAF-YOLO,":[30],"a":[31,104,115,146],"lightweight":[32,95],"unsafe-behavior":[33,111],"framework":[35],"based":[36],"on":[37,114],"YOLOv11":[38,134],"for":[39,108],"cigarette":[40],"manufacturing":[41],"scenarios.":[42],"ORAF-YOLO":[43,120,144],"integrates":[44],"four":[45],"coordinated":[46],"improvements:":[47],"SEAM":[48],"enhances":[49],"critical":[50],"local":[51],"features":[52],"under":[53],"CGA-Fusion":[55],"improves":[56,77],"adaptive":[57],"multi-level":[58],"feature":[59,73,91,93],"aggregation":[60],"while":[61,71,135],"suppressing":[62],"background":[63],"interference,":[64],"grouped":[65],"dual-kernel":[66],"convolution":[67],"reduces":[68],"computational":[69],"cost":[70],"preserving":[72],"representation,":[74],"SlideLoss":[76],"convergence":[78],"stability":[79],"by":[80],"dynamically":[81],"reweighting":[82],"samples":[83],"of":[84],"different":[85],"difficulty":[86],"levels.":[87],"By":[88],"jointly":[89],"optimizing":[90],"enhancement,":[92],"fusion,":[94],"computation,":[96],"training":[98],"strategy,":[99],"the":[100,132],"proposed":[101],"method":[102],"provides":[103],"more":[105],"complete":[106],"solution":[107],"industrial":[110,158],"recognition.":[112],"Experiments":[113],"self-constructed":[116],"dataset":[117],"show":[118],"that":[119,143],"achieves":[121,145],"89.5%":[122],"Precision,":[123],"94.2%":[124],"mAP50,":[125],"68.4%":[126],"mAP50&#x2013;95,":[127],"64.20":[129],"FPS,":[130],"outperforming":[131],"original":[133],"maintaining":[136],"inference":[138],"capability.":[139],"These":[140],"results":[141],"demonstrate":[142],"favorable":[147],"balance":[148],"among":[149],"accuracy,":[151],"robustness,":[152],"deployment":[154],"efficiency":[155],"environments.":[159]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-05-16T08:24:45.110214","created_date":"2026-05-01T00:00:00"}
