{"id":"https://openalex.org/W4284897674","doi":"https://doi.org/10.1145/3534572","title":"Acceleration-based Activity Recognition of Repetitive Works with Lightweight Ordered-work Segmentation Network","display_name":"Acceleration-based Activity Recognition of Repetitive Works with Lightweight Ordered-work Segmentation Network","publication_year":2022,"publication_date":"2022-07-04","ids":{"openalex":"https://openalex.org/W4284897674","doi":"https://doi.org/10.1145/3534572"},"language":"en","primary_location":{"id":"doi:10.1145/3534572","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3534572","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3534572","source":{"id":"https://openalex.org/S4210219751","display_name":"Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies","issn_l":"2474-9567","issn":["2474-9567"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3534572","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045581069","display_name":"Naoya Yoshimura","orcid":"https://orcid.org/0000-0003-3017-8873"},"institutions":[{"id":"https://openalex.org/I98285908","display_name":"The University of Osaka","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Naoya Yoshimura","raw_affiliation_strings":["Osaka University, Graduate School of Information Science and Technology, Suita, Osaka, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Osaka University, Graduate School of Information Science and Technology, Suita, Osaka, Japan","institution_ids":["https://openalex.org/I98285908"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039456378","display_name":"Takuya Maekawa","orcid":"https://orcid.org/0000-0002-7227-580X"},"institutions":[{"id":"https://openalex.org/I98285908","display_name":"The University of Osaka","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takuya Maekawa","raw_affiliation_strings":["Osaka University, Graduate School of Information Science and Technology, Suita, Osaka, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Osaka University, Graduate School of Information Science and Technology, Suita, Osaka, Japan","institution_ids":["https://openalex.org/I98285908"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012025870","display_name":"Takahiro Hara","orcid":"https://orcid.org/0000-0003-4807-3156"},"institutions":[{"id":"https://openalex.org/I98285908","display_name":"The University of Osaka","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takahiro Hara","raw_affiliation_strings":["Osaka University, Graduate School of Information Science and Technology, Suita, Osaka, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Osaka University, Graduate School of Information Science and Technology, Suita, Osaka, Japan","institution_ids":["https://openalex.org/I98285908"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001104972","display_name":"Atsushi Wada","orcid":"https://orcid.org/0000-0003-2218-1677"},"institutions":[{"id":"https://openalex.org/I1292669757","display_name":"Toshiba (Japan)","ror":"https://ror.org/0326v3z14","country_code":"JP","type":"company","lineage":["https://openalex.org/I1292669757"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Atsushi Wada","raw_affiliation_strings":["Toshiba Corporation, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Toshiba Corporation, Japan","institution_ids":["https://openalex.org/I1292669757"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043472678","display_name":"Yasuo Namioka","orcid":null},"institutions":[{"id":"https://openalex.org/I1292669757","display_name":"Toshiba (Japan)","ror":"https://ror.org/0326v3z14","country_code":"JP","type":"company","lineage":["https://openalex.org/I1292669757"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yasuo Namioka","raw_affiliation_strings":["Toshiba Corporation, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Toshiba Corporation, Japan","institution_ids":["https://openalex.org/I1292669757"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.5449,"has_fulltext":true,"cited_by_count":27,"citation_normalized_percentile":{"value":0.9089337,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"6","issue":"2","first_page":"1","last_page":"39"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9987000226974487,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9987000226974487,"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/T10525","display_name":"Human-Automation Interaction and Safety","score":0.9797999858856201,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.97079998254776,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/activity-recognition","display_name":"Activity recognition","score":0.8396933078765869},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7884668111801147},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6884209513664246},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.598362147808075},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5660173296928406},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5586696267127991},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5063751935958862},{"id":"https://openalex.org/keywords/accelerometer","display_name":"Accelerometer","score":0.5043884515762329},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.4948806166648865},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4818047881126404},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47512203454971313},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3575438857078552},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3417302966117859},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3355557918548584}],"concepts":[{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.8396933078765869},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7884668111801147},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6884209513664246},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.598362147808075},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5660173296928406},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5586696267127991},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5063751935958862},{"id":"https://openalex.org/C89805583","wikidata":"https://www.wikidata.org/wiki/Q192940","display_name":"Accelerometer","level":2,"score":0.5043884515762329},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.4948806166648865},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4818047881126404},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47512203454971313},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3575438857078552},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3417302966117859},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3355557918548584},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3534572","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3534572","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3534572","source":{"id":"https://openalex.org/S4210219751","display_name":"Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies","issn_l":"2474-9567","issn":["2474-9567"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3534572","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3534572","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3534572","source":{"id":"https://openalex.org/S4210219751","display_name":"Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies","issn_l":"2474-9567","issn":["2474-9567"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1715226951","display_name":null,"funder_award_id":"JP21H05299","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G1936760464","display_name":null,"funder_award_id":"21H05293","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G2894010033","display_name":"Driver-less skill assessment and analysis using explainable AI","funder_award_id":"21K19769","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G3078911313","display_name":null,"funder_award_id":"ACT-X JPMJAX200T","funder_id":"https://openalex.org/F4320334789","funder_display_name":"Japan Science and Technology Agency"},{"id":"https://openalex.org/G3254300394","display_name":null,"funder_award_id":"JP21H03428","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G5843561013","display_name":"\u30a6\u30a7\u30a2\u30e9\u30d6\u30eb\u30bb\u30f3\u30b5\u3092\u7528\u3044\u305fOne-model-fits-all\u884c\u52d5\u8a8d\u8b58\u306e\u7814\u7a76\u958b\u767a","funder_award_id":"21J10059","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G6439734173","display_name":null,"funder_award_id":"JP21H03428, JP21H05299, JP21J10059","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G8155463449","display_name":null,"funder_award_id":"21H05299","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G886700912","display_name":null,"funder_award_id":"JP21H03428, JP21H05299, and JP21J10059","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"},{"id":"https://openalex.org/F4320334789","display_name":"Japan Science and Technology Agency","ror":"https://ror.org/00097mb19"},{"id":"https://openalex.org/F4320338246","display_name":"ACT-X","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4284897674.pdf","grobid_xml":"https://content.openalex.org/works/W4284897674.grobid-xml"},"referenced_works_count":52,"referenced_works":["https://openalex.org/W23024595","https://openalex.org/W123295786","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2026297770","https://openalex.org/W2114506737","https://openalex.org/W2126511896","https://openalex.org/W2144348409","https://openalex.org/W2144691514","https://openalex.org/W2157091296","https://openalex.org/W2194775991","https://openalex.org/W2219995598","https://openalex.org/W2270470215","https://openalex.org/W2345270026","https://openalex.org/W2412782625","https://openalex.org/W2473781013","https://openalex.org/W2548335893","https://openalex.org/W2592284297","https://openalex.org/W2626046541","https://openalex.org/W2751594996","https://openalex.org/W2755982260","https://openalex.org/W2790871235","https://openalex.org/W2883074505","https://openalex.org/W2891539715","https://openalex.org/W2894702700","https://openalex.org/W2897077592","https://openalex.org/W2907279499","https://openalex.org/W2930120178","https://openalex.org/W2944740725","https://openalex.org/W2948204427","https://openalex.org/W2962728655","https://openalex.org/W2963307106","https://openalex.org/W2964098128","https://openalex.org/W2964309882","https://openalex.org/W2973102973","https://openalex.org/W2978253059","https://openalex.org/W2996715881","https://openalex.org/W2998347490","https://openalex.org/W2999219213","https://openalex.org/W3005408728","https://openalex.org/W3007287549","https://openalex.org/W3044644239","https://openalex.org/W3083281679","https://openalex.org/W3090204015","https://openalex.org/W3095396592","https://openalex.org/W3120335880","https://openalex.org/W3162237909","https://openalex.org/W4230665386","https://openalex.org/W4247330045","https://openalex.org/W4251033893","https://openalex.org/W6888877617","https://openalex.org/W6967585634"],"related_works":["https://openalex.org/W2765080098","https://openalex.org/W2385749422","https://openalex.org/W2355290145","https://openalex.org/W2353465659","https://openalex.org/W2009888974","https://openalex.org/W4384517610","https://openalex.org/W4288389100","https://openalex.org/W1902800522","https://openalex.org/W2339469482","https://openalex.org/W2706752825"],"abstract_inverted_index":{"This":[0,181],"study":[1],"presents":[2],"a":[3,27,33,43,48,78,94,135,187,238],"new":[4],"neural":[5],"network":[6],"model":[7],"for":[8,76,119,176],"recognizing":[9,177],"manual":[10,155],"works":[11,156],"using":[12,197,228],"body-worn":[13],"accelerometers":[14],"in":[15,47,67,103,137,234],"industrial":[16,25,68],"settings,":[17],"named":[18],"Lightweight":[19],"Ordered-work":[20],"Segmentation":[21],"Network":[22],"(LOS-Net).":[23],"In":[24,84],"domains,":[26],"human":[28],"worker":[29],"typically":[30],"repetitively":[31],"performs":[32],"set":[34],"of":[35,42,45,71,81,97,122,148,219,225],"predefined":[36,49],"processes,":[37],"with":[38,144],"each":[39],"process":[40],"consisting":[41],"sequence":[44],"activities":[46,140],"order.":[50],"State-of-the-art":[51],"activity":[52,207],"recognition":[53,121],"models,":[54,58],"such":[55],"as":[56],"encoder-decoder":[57],"have":[59],"numerous":[60],"trainable":[61,108,199],"parameters,":[62],"making":[63],"their":[64],"training":[65,98],"difficult":[66],"domains":[69],"because":[70,134],"the":[72,86,101,104,116,128,138,145,149,154,162,168,178,202,206,210,217,223,226],"consequent":[73],"substantial":[74],"cost":[75],"preparing":[77],"large":[79],"amount":[80,96],"labeled":[82],"data.":[83,99],"contrast,":[85],"LOS-Net":[87,105,203,227],"is":[88,111,141,174,183],"designed":[89,112],"to":[90,113],"be":[91],"trained":[92],"on":[93],"limited":[95],"Specifically,":[100],"decoder":[102,211],"has":[106],"few":[107,198],"parameters":[109],"and":[110,157,170,237,241],"capture":[114],"only":[115],"necessary":[117],"information":[118,130,166,182],"precise":[120],"ordered":[123,163],"works.":[124],"These":[125],"are":[126],"(i)":[127],"boundary":[129],"between":[131],"consecutive":[132],"activities,":[133],"transition":[136],"performed":[139],"generally":[142],"associated":[143],"trend":[146],"change":[147],"sensor":[150,229],"data":[151,230],"collected":[152,231],"during":[153],"(ii)":[158],"long-term":[159],"context":[160],"regarding":[161,216],"works,":[164],"e.g.,":[165],"about":[167],"previous":[169],"next":[171],"activity,":[172],"which":[173],"useful":[175],"current":[179],"activity.":[180],"obtained":[184],"by":[185,209,212],"introducing":[186],"module":[188],"that":[189,243],"can":[190,204,245],"collect":[191],"it":[192,244],"at":[193],"distant":[194],"time":[195],"steps":[196],"parameters.":[200],"Moreover,":[201],"refine":[205],"estimation":[208],"incorporating":[213],"prior":[214],"knowledge":[215],"order":[218],"activities.":[220],"We":[221],"demonstrate":[222],"effectiveness":[224],"from":[232],"workers":[233],"actual":[235],"factories":[236],"logistics":[239],"center,":[240],"show":[242],"achieve":[246],"state-of-the-art":[247],"performance.":[248]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-13T07:31:44.756512","created_date":"2025-10-10T00:00:00"}