{"id":"https://openalex.org/W4221150469","doi":"https://doi.org/10.1109/percomworkshops53856.2022.9767342","title":"HAR-GCNN: Deep Graph CNNs for Human Activity Recognition From Highly Unlabeled Mobile Sensor Data","display_name":"HAR-GCNN: Deep Graph CNNs for Human Activity Recognition From Highly Unlabeled Mobile Sensor Data","publication_year":2022,"publication_date":"2022-03-21","ids":{"openalex":"https://openalex.org/W4221150469","doi":"https://doi.org/10.1109/percomworkshops53856.2022.9767342"},"language":"en","primary_location":{"id":"doi:10.1109/percomworkshops53856.2022.9767342","is_oa":false,"landing_page_url":"https://doi.org/10.1109/percomworkshops53856.2022.9767342","pdf_url":null,"source":{"id":"https://openalex.org/S4363608020","display_name":"2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)","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 Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2203.03087","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5024293473","display_name":"Abduallah Mohamed","orcid":null},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Abduallah Mohamed","raw_affiliation_strings":["The University of Texas,Austin","The University of Texas, Austin"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Texas,Austin","institution_ids":["https://openalex.org/I86519309"]},{"raw_affiliation_string":"The University of Texas, Austin","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017319951","display_name":"Fernando Lejarza","orcid":"https://orcid.org/0000-0002-5022-4390"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fernando Lejarza","raw_affiliation_strings":["The University of Texas,Austin","The University of Texas, Austin"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Texas,Austin","institution_ids":["https://openalex.org/I86519309"]},{"raw_affiliation_string":"The University of Texas, Austin","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040389195","display_name":"Stephanie Cahail","orcid":null},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Stephanie Cahail","raw_affiliation_strings":["The University of Texas,Austin","The University of Texas, Austin"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Texas,Austin","institution_ids":["https://openalex.org/I86519309"]},{"raw_affiliation_string":"The University of Texas, Austin","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082935103","display_name":"Christian Claudel","orcid":"https://orcid.org/0000-0002-3783-4928"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christian Claudel","raw_affiliation_strings":["The University of Texas,Austin","The University of Texas, Austin"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Texas,Austin","institution_ids":["https://openalex.org/I86519309"]},{"raw_affiliation_string":"The University of Texas, Austin","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025977484","display_name":"Edison Thomaz","orcid":"https://orcid.org/0000-0001-8188-0457"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Edison Thomaz","raw_affiliation_strings":["The University of Texas,Austin","The University of Texas, Austin"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Texas,Austin","institution_ids":["https://openalex.org/I86519309"]},{"raw_affiliation_string":"The University of Texas, Austin","institution_ids":["https://openalex.org/I86519309"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I86519309"],"apc_list":null,"apc_paid":null,"fwci":1.0171,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.84499685,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"335","last_page":"340"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9998999834060669,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9825000166893005,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9641000032424927,"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/activity-recognition","display_name":"Activity recognition","score":0.8454928398132324},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.778795063495636},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.6610716581344604},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6192765831947327},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6101388931274414},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5295805931091309},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4459793269634247},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.4430214762687683},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4412250518798828},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.41464120149612427},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3473154902458191}],"concepts":[{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.8454928398132324},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.778795063495636},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.6610716581344604},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6192765831947327},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6101388931274414},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5295805931091309},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4459793269634247},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.4430214762687683},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4412250518798828},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.41464120149612427},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3473154902458191},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/percomworkshops53856.2022.9767342","is_oa":false,"landing_page_url":"https://doi.org/10.1109/percomworkshops53856.2022.9767342","pdf_url":null,"source":{"id":"https://openalex.org/S4363608020","display_name":"2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)","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 Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2203.03087","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2203.03087","pdf_url":"https://arxiv.org/pdf/2203.03087","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2203.03087","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2203.03087","pdf_url":"https://arxiv.org/pdf/2203.03087","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4221150469.pdf","grobid_xml":"https://content.openalex.org/works/W4221150469.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W1527911497","https://openalex.org/W1600744878","https://openalex.org/W1677182931","https://openalex.org/W1762028752","https://openalex.org/W2002261403","https://openalex.org/W2017634428","https://openalex.org/W2023302299","https://openalex.org/W2026297770","https://openalex.org/W2136010533","https://openalex.org/W2550797816","https://openalex.org/W2571410400","https://openalex.org/W2604630936","https://openalex.org/W2619606157","https://openalex.org/W2736191430","https://openalex.org/W2751594996","https://openalex.org/W2770106921","https://openalex.org/W2783920628","https://openalex.org/W2803675191","https://openalex.org/W2897943474","https://openalex.org/W2905224888","https://openalex.org/W2940963663","https://openalex.org/W2961553857","https://openalex.org/W2963373106","https://openalex.org/W2963855167","https://openalex.org/W2964015378","https://openalex.org/W2964062686","https://openalex.org/W2971670291","https://openalex.org/W2990045899","https://openalex.org/W2998662742","https://openalex.org/W3002916757","https://openalex.org/W3015356384","https://openalex.org/W3035096461","https://openalex.org/W3152893301","https://openalex.org/W6704286305","https://openalex.org/W6726873649"],"related_works":["https://openalex.org/W2361861616","https://openalex.org/W2263699433","https://openalex.org/W2377979023","https://openalex.org/W2218034408","https://openalex.org/W2392921965","https://openalex.org/W2383111961","https://openalex.org/W2365952365","https://openalex.org/W2358755282","https://openalex.org/W2124823771","https://openalex.org/W2610740816"],"abstract_inverted_index":{"The":[0],"problem":[1],"of":[2,63],"human":[3,31,76],"activity":[4,32,43,134,149],"recognition":[5,33],"from":[6],"mobile":[7],"sensor":[8,119],"data":[9,36],"applies":[10],"to":[11,47,75,93,121,161,174],"multiple":[12],"domains,":[13],"such":[14],"as":[15],"health":[16],"monitoring,":[17],"personal":[18],"fitness,":[19],"daily":[20],"life":[21],"logging,":[22],"and":[23,50,97,172],"senior":[24],"care.":[25],"A":[26],"critical":[27],"challenge":[28],"for":[29,126],"training":[30,140],"models":[34],"is":[35,70],"quality.":[37],"Acquiring":[38],"balanced":[39],"datasets":[40],"containing":[41],"accurate":[42],"labels":[44,96,125,150],"requires":[45],"humans":[46],"correctly":[48],"annotate":[49],"potentially":[51],"interfere":[52],"with":[53],"the":[54,61,114,123,144,147,153],"subjects’":[55],"normal":[56],"activities":[57,128],"in":[58],"real-time.":[59],"Despite":[60],"likelihood":[62],"incorrect":[64],"annotation":[65],"or":[66],"lack":[67],"thereof,":[68],"there":[69],"often":[71],"an":[72],"inherent":[73],"chronology":[74,89],"behavior.":[77],"For":[78],"example,":[79],"we":[80,85,104],"take":[81],"a":[82,107,138],"shower":[83],"after":[84],"exercise.":[86],"This":[87],"implicit":[88],"can":[90],"be":[91],"used":[92,163],"learn":[94],"unknown":[95],"classify":[98],"future":[99],"activities.":[100],"In":[101],"this":[102],"work,":[103],"propose":[105,137],"HAR-GCCN,":[106],"deep":[108],"graph":[109],"CNN":[110],"model":[111,145],"that":[112,129,143],"leverages":[113],"correlation":[115],"between":[116],"chronologically":[117],"adjacent":[118],"measurements":[120],"predict":[122],"correct":[124],"unclassified":[127],"have":[130],"at":[131],"least":[132],"one":[133],"label.":[135],"We":[136],"new":[139],"strategy":[141],"enforcing":[142],"predicts":[146],"missing":[148],"by":[151,169],"leveraging":[152],"known":[154],"ones.":[155],"HAR-GCCN":[156],"shows":[157],"superior":[158],"performance":[159],"relative":[160],"previously":[162],"baseline":[164],"methods,":[165],"improving":[166],"classification":[167],"accuracy":[168],"about":[170],"25%":[171],"up":[173],"68%":[175],"on":[176],"different":[177],"datasets.":[178]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}