{"id":"https://openalex.org/W7138837245","doi":"https://doi.org/10.1109/kst67832.2026.11432375","title":"Impact of Background Removal and Pose on Deep Learning Industrial Action Recognition","display_name":"Impact of Background Removal and Pose on Deep Learning Industrial Action Recognition","publication_year":2026,"publication_date":"2026-01-21","ids":{"openalex":"https://openalex.org/W7138837245","doi":"https://doi.org/10.1109/kst67832.2026.11432375"},"language":null,"primary_location":{"id":"doi:10.1109/kst67832.2026.11432375","is_oa":false,"landing_page_url":"https://doi.org/10.1109/kst67832.2026.11432375","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 18th International Conference on Knowledge and Smart Technology (KST)","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/A5087962449","display_name":"C. C. Yang","orcid":"https://orcid.org/0000-0002-3476-3802"},"institutions":[{"id":"https://openalex.org/I154864474","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49","country_code":"TW","type":"education","lineage":["https://openalex.org/I154864474"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chao-Lung Yang","raw_affiliation_strings":["National Taiwan University of Science and Technology,Department of Industrial Management,Taipei,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taiwan University of Science and Technology,Department of Industrial Management,Taipei,Taiwan","institution_ids":["https://openalex.org/I154864474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079626839","display_name":"Shu-Hao Liang","orcid":"https://orcid.org/0000-0002-4409-3507"},"institutions":[{"id":"https://openalex.org/I118292597","display_name":"National Taipei University of Technology","ror":"https://ror.org/00cn92c09","country_code":"TW","type":"education","lineage":["https://openalex.org/I118292597"]},{"id":"https://openalex.org/I154864474","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49","country_code":"TW","type":"education","lineage":["https://openalex.org/I154864474"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Shu-Hao Liang","raw_affiliation_strings":["Graduate Institute of Intelligent Manufacturing, National Taiwan University of Science and Technology,Taipei,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate Institute of Intelligent Manufacturing, National Taiwan University of Science and Technology,Taipei,Taiwan","institution_ids":["https://openalex.org/I118292597","https://openalex.org/I154864474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122745937","display_name":"Po Ting Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I154864474","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49","country_code":"TW","type":"education","lineage":["https://openalex.org/I154864474"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Po Ting Lin","raw_affiliation_strings":["National Taiwan University of Science and Technology,Department of Industrial Management,Taipei,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taiwan University of Science and Technology,Department of Industrial Management,Taipei,Taiwan","institution_ids":["https://openalex.org/I154864474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130142721","display_name":"Zi-Shan Hsiao","orcid":null},"institutions":[{"id":"https://openalex.org/I154864474","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49","country_code":"TW","type":"education","lineage":["https://openalex.org/I154864474"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Zi-Shan Hsiao","raw_affiliation_strings":["National Taiwan University of Science and Technology,Department of Industrial Management,Taipei,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taiwan University of Science and Technology,Department of Industrial Management,Taipei,Taiwan","institution_ids":["https://openalex.org/I154864474"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087418950","display_name":"Ting-Yi Yen","orcid":null},"institutions":[{"id":"https://openalex.org/I154864474","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49","country_code":"TW","type":"education","lineage":["https://openalex.org/I154864474"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Ting-Yi Yen","raw_affiliation_strings":["National Taiwan University of Science and Technology,Department of Industrial Management,Taipei,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taiwan University of Science and Technology,Department of Industrial Management,Taipei,Taiwan","institution_ids":["https://openalex.org/I154864474"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"46","last_page":"52"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9258000254631042,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9258000254631042,"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":0.006800000090152025,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.00570000009611249,"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/deep-learning","display_name":"Deep learning","score":0.7067999839782715},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6722000241279602},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6503999829292297},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5931000113487244},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5224000215530396},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.44020000100135803},{"id":"https://openalex.org/keywords/entertainment-industry","display_name":"Entertainment industry","score":0.38269999623298645},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.34709998965263367}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8044999837875366},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7301999926567078},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7067999839782715},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6722000241279602},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6503999829292297},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5931000113487244},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5224000215530396},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.47200000286102295},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4611000120639801},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.44020000100135803},{"id":"https://openalex.org/C2985708247","wikidata":"https://www.wikidata.org/wiki/Q173799","display_name":"Entertainment industry","level":3,"score":0.38269999623298645},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.34709998965263367},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.33250001072883606},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.328000009059906},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.32760000228881836},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.31679999828338623},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.29019999504089355},{"id":"https://openalex.org/C2944601119","wikidata":"https://www.wikidata.org/wiki/Q43744058","display_name":"Residual neural network","level":3,"score":0.27810001373291016},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.25459998846054077},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.2538999915122986},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.25290000438690186}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/kst67832.2026.11432375","is_oa":false,"landing_page_url":"https://doi.org/10.1109/kst67832.2026.11432375","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 18th International Conference on Knowledge and Smart Technology (KST)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6674461433","display_name":null,"funder_award_id":"113-2221-E-011-130-MY2,113-2218-E-011-002","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"}],"funders":[{"id":"https://openalex.org/F4320322795","display_name":"Ministry of Science and Technology, Taiwan","ror":"https://ror.org/02kv4zf79"},{"id":"https://openalex.org/F4320324515","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0],"paper":[1],"investigates":[2],"the":[3,26],"impact":[4],"of":[5],"background":[6,43,140],"removal":[7,44,141],"techniques":[8],"on":[9,23,37,71,145],"deep":[10],"learning":[11],"models":[12,59],"for":[13,90,117,134],"industrial":[14,38,73],"action":[15],"recognition.":[16],"Unlike":[17],"previous":[18],"studies":[19],"that":[20],"mainly":[21],"focus":[22,144],"daily":[24],"activities,":[25],"fashion":[27],"industry":[28],"or":[29],"entertainment":[30],"scenarios":[31],"[1],":[32],"[2],":[33],"our":[34],"work":[35],"centers":[36],"settings.":[39],"We":[40],"evaluate":[41],"three":[42,57],"methods":[45],"(Mask":[46,51],"Region-based":[47],"Convolutional":[48],"Neural":[49],"Network":[50],"R-CNN),":[52],"MediaPipe,":[53],"rembg)":[54],"combined":[55],"with":[56,80],"temporal":[58],"(Inflated":[60],"3D":[61,65],"ConvNet":[62],"(I3D)":[63],"[3],":[64],"ResNet":[66],"(R3D)":[67],"[4],":[68],"SlowFast":[69],"[5])":[70],"six":[72],"actions.":[74],"Results":[75],"demonstrate":[76],"significant":[77],"performance":[78],"improvements,":[79],"rembg":[81],"+":[82,125],"I3D":[83],"achieving":[84],"97.54%":[85],"accuracy":[86,129],"compared":[87],"to":[88],"77.26%":[89],"original":[91],"video":[92],"input.":[93],"The":[94,137],"study":[95,138],"also":[96],"examines":[97],"robustness":[98],"under":[99],"noise":[100],"and":[101],"blur":[102],"conditions,":[103],"showing":[104],"background-removed":[105],"inputs":[106],"maintain":[107],"superior":[108],"performance.":[109],"Inference":[110],"time":[111],"analysis":[112],"reveals":[113],"optimal":[114],"accuracy-speed":[115],"trade-offs":[116],"different":[118],"deployment":[119],"scenarios.":[120],"Among":[121],"them,":[122],"Mask":[123],"R-CNN":[124],"R3D":[126],"achieves":[127],"90.41%":[128],"in":[130],"0.77":[131],"s,":[132],"suitable":[133],"edge":[135],"deployment.":[136],"confirms":[139],"enhances":[142],"model":[143],"relevant":[146],"motion":[147],"patterns":[148],"while":[149],"reducing":[150],"environmental":[151],"interference.":[152]},"counts_by_year":[],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2026-03-20T00:00:00"}