{"id":"https://openalex.org/W4200451791","doi":"https://doi.org/10.3390/s22010174","title":"Robust Human Activity Recognition by Integrating Image and Accelerometer Sensor Data Using Deep Fusion Network","display_name":"Robust Human Activity Recognition by Integrating Image and Accelerometer Sensor Data Using Deep Fusion Network","publication_year":2021,"publication_date":"2021-12-28","ids":{"openalex":"https://openalex.org/W4200451791","doi":"https://doi.org/10.3390/s22010174","pmid":"https://pubmed.ncbi.nlm.nih.gov/35009717"},"language":"en","primary_location":{"id":"doi:10.3390/s22010174","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22010174","pdf_url":"https://www.mdpi.com/1424-8220/22/1/174/pdf?version=1640681782","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/22/1/174/pdf?version=1640681782","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022472066","display_name":"Junhyuk Kang","orcid":"https://orcid.org/0000-0002-9349-960X"},"institutions":[{"id":"https://openalex.org/I12832649","display_name":"Gachon University","ror":"https://ror.org/03ryywt80","country_code":"KR","type":"education","lineage":["https://openalex.org/I12832649"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Junhyuk Kang","raw_affiliation_strings":["Department of Software, Gachon University, Seongnam 13120, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Software, Gachon University, Seongnam 13120, Korea","institution_ids":["https://openalex.org/I12832649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019049830","display_name":"Ji-eun Shin","orcid":"https://orcid.org/0000-0002-3456-8599"},"institutions":[{"id":"https://openalex.org/I12832649","display_name":"Gachon University","ror":"https://ror.org/03ryywt80","country_code":"KR","type":"education","lineage":["https://openalex.org/I12832649"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jieun Shin","raw_affiliation_strings":["Department of Software, Gachon University, Seongnam 13120, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Software, Gachon University, Seongnam 13120, Korea","institution_ids":["https://openalex.org/I12832649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028056896","display_name":"Jaewon Shin","orcid":"https://orcid.org/0000-0001-5272-3081"},"institutions":[{"id":"https://openalex.org/I12832649","display_name":"Gachon University","ror":"https://ror.org/03ryywt80","country_code":"KR","type":"education","lineage":["https://openalex.org/I12832649"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jaewon Shin","raw_affiliation_strings":["Department of Software, Gachon University, Seongnam 13120, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Software, Gachon University, Seongnam 13120, Korea","institution_ids":["https://openalex.org/I12832649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032173768","display_name":"Daeho Lee","orcid":"https://orcid.org/0000-0002-8119-9677"},"institutions":[{"id":"https://openalex.org/I12832649","display_name":"Gachon University","ror":"https://ror.org/03ryywt80","country_code":"KR","type":"education","lineage":["https://openalex.org/I12832649"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Daeho Lee","raw_affiliation_strings":["Department of Mechanical Engineering, Gachon University, Seongnam 13120, Korea"],"raw_orcid":"https://orcid.org/0000-0002-8119-9677","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, Gachon University, Seongnam 13120, Korea","institution_ids":["https://openalex.org/I12832649"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000021330","display_name":"Ahyoung Choi","orcid":"https://orcid.org/0000-0001-7676-9869"},"institutions":[{"id":"https://openalex.org/I12832649","display_name":"Gachon University","ror":"https://ror.org/03ryywt80","country_code":"KR","type":"education","lineage":["https://openalex.org/I12832649"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Ahyoung Choi","raw_affiliation_strings":["Department of Software, Gachon University, Seongnam 13120, Korea"],"raw_orcid":"https://orcid.org/0000-0001-7676-9869","affiliations":[{"raw_affiliation_string":"Department of Software, Gachon University, Seongnam 13120, Korea","institution_ids":["https://openalex.org/I12832649"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5000021330"],"corresponding_institution_ids":["https://openalex.org/I12832649"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":1.2611,"has_fulltext":true,"cited_by_count":22,"citation_normalized_percentile":{"value":0.82366511,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"22","issue":"1","first_page":"174","last_page":"174"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9991000294685364,"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":0.9991000294685364,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9915000200271606,"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/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9767000079154968,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/accelerometer","display_name":"Accelerometer","score":0.8038922548294067},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7342315912246704},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7158540487289429},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6942441463470459},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6886777877807617},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5469799041748047},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.501333475112915},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.46332496404647827},{"id":"https://openalex.org/keywords/data-pre-processing","display_name":"Data pre-processing","score":0.45716938376426697},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.4404981732368469},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.42003333568573},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4139675498008728},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.38825350999832153},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3206366300582886},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2277052104473114},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.10947087407112122}],"concepts":[{"id":"https://openalex.org/C89805583","wikidata":"https://www.wikidata.org/wiki/Q192940","display_name":"Accelerometer","level":2,"score":0.8038922548294067},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7342315912246704},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7158540487289429},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6942441463470459},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6886777877807617},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5469799041748047},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.501333475112915},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.46332496404647827},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.45716938376426697},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.4404981732368469},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.42003333568573},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4139675498008728},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38825350999832153},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3206366300582886},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2277052104473114},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.10947087407112122},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006802","descriptor_name":"Human Activities","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006802","descriptor_name":"Human Activities","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006802","descriptor_name":"Human Activities","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D061725","descriptor_name":"Accelerometry","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D061725","descriptor_name":"Accelerometry","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D061725","descriptor_name":"Accelerometry","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":5,"locations":[{"id":"doi:10.3390/s22010174","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22010174","pdf_url":"https://www.mdpi.com/1424-8220/22/1/174/pdf?version=1640681782","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:35009717","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35009717","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:8eb8597803e04fbf99af823ff914e63a","is_oa":true,"landing_page_url":"https://doaj.org/article/8eb8597803e04fbf99af823ff914e63a","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":"Sensors, Vol 22, Iss 1, p 174 (2021)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/22/1/174/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s22010174","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"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":"Sensors; Volume 22; Issue 1; Pages: 174","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:8747696","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8747696","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"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":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s22010174","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22010174","pdf_url":"https://www.mdpi.com/1424-8220/22/1/174/pdf?version=1640681782","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1960212446","display_name":null,"funder_award_id":"NRF-2021R1F1A1062181","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G8523083134","display_name":null,"funder_award_id":"GCU-2019-0386","funder_id":"https://openalex.org/F4320321366","funder_display_name":"Gachon University"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320321366","display_name":"Gachon University","ror":"https://ror.org/03ryywt80"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4200451791.pdf","grobid_xml":"https://content.openalex.org/works/W4200451791.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W1481162702","https://openalex.org/W2064675550","https://openalex.org/W2076063813","https://openalex.org/W2143043296","https://openalex.org/W2146199357","https://openalex.org/W2217325140","https://openalex.org/W2269209296","https://openalex.org/W2270470215","https://openalex.org/W2342311830","https://openalex.org/W2548437830","https://openalex.org/W2759690896","https://openalex.org/W2791422233","https://openalex.org/W2795342689","https://openalex.org/W2802503116","https://openalex.org/W2884585870","https://openalex.org/W2898855010","https://openalex.org/W2901087326","https://openalex.org/W2932653737","https://openalex.org/W2963993350","https://openalex.org/W2969552585","https://openalex.org/W2974089216","https://openalex.org/W2998376881","https://openalex.org/W3001316388","https://openalex.org/W3033554701","https://openalex.org/W3195795483","https://openalex.org/W3198221794","https://openalex.org/W4237074696","https://openalex.org/W6680977888","https://openalex.org/W6687483927","https://openalex.org/W6743447383","https://openalex.org/W6772938244","https://openalex.org/W6800492434"],"related_works":["https://openalex.org/W2989490741","https://openalex.org/W3092506759","https://openalex.org/W2367545121","https://openalex.org/W4248881655","https://openalex.org/W2482165163","https://openalex.org/W3010890513","https://openalex.org/W120741642","https://openalex.org/W138569904","https://openalex.org/W2390914021","https://openalex.org/W2389417819"],"abstract_inverted_index":{"Studies":[0],"on":[1,48],"deep-learning-based":[2],"behavioral":[3],"pattern":[4],"recognition":[5],"have":[6],"recently":[7],"received":[8],"considerable":[9],"attention.":[10],"However,":[11],"if":[12],"there":[13],"are":[14],"insufficient":[15],"data":[16,144,183,189],"and":[17,90,105,112,118,132,135,142,171,187],"the":[18,72,150,158,161,178,192],"activity":[19],"to":[20,44,165,177],"be":[21,31,166],"identified":[22],"is":[23,42],"changed,":[24],"a":[25,36,55,77,100,119,129,138,198],"robust":[26,43],"deep":[27,38,56,79],"learning":[28,39,57,80],"model":[29,40,58,81,194],"cannot":[30],"created.":[32],"This":[33],"work":[34],"contributes":[35],"generalized":[37],"that":[41,64,82,184,191],"noise":[45,175,188],"not":[46],"dependent":[47],"input":[49,62,73],"signals":[50],"by":[51],"extracting":[52],"features":[53],"through":[54],"for":[59],"each":[60],"heterogeneous":[61,84],"signal":[63],"can":[65],"maintain":[66],"performance":[67,199],"while":[68],"minimizing":[69],"preprocessing":[70],"of":[71,160,201],"signal.":[74],"We":[75],"propose":[76],"hybrid":[78],"takes":[83],"sensor":[85],"data,":[86,97,134],"an":[87,91],"acceleration":[88],"sensor,":[89],"image":[92,131],"as":[93],"inputs.":[94],"For":[95],"accelerometer":[96,133,143,179],"we":[98],"use":[99],"convolutional":[101,106],"neural":[102,121],"network":[103],"(CNN)":[104],"block":[107],"attention":[108],"module":[109],"models":[110],"(CBAM),":[111],"apply":[113],"bidirectional":[114],"long":[115],"short-term":[116],"memory":[117],"residual":[120],"network.":[122],"The":[123],"overall":[124],"accuracy":[125,159],"was":[126,163,195],"94.8%":[127],"with":[128,137,168,173,182,197],"skeleton":[130,139],"93.1%":[136],"image,":[140],"coordinates,":[141],"after":[145],"evaluating":[146],"nine":[147],"behaviors":[148],"using":[149],"Berkeley":[151],"Multimodal":[152],"Human":[153],"Action":[154],"Database":[155],"(MHAD).":[156],"Furthermore,":[157],"investigation":[162],"revealed":[164],"93.4%":[167],"inverted":[169],"images":[170],"93.2%":[172],"white":[174],"added":[176],"data.":[180],"Testing":[181],"included":[185],"inversion":[186],"indicated":[190],"suggested":[193],"robust,":[196],"deterioration":[200],"approximately":[202],"1%.":[203]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":1}],"updated_date":"2026-06-09T15:46:55.921056","created_date":"2025-10-10T00:00:00"}