{"id":"https://openalex.org/W2548765505","doi":"https://doi.org/10.1145/2994551.2994569","title":"Deep Learning for RFID-Based Activity Recognition","display_name":"Deep Learning for RFID-Based Activity Recognition","publication_year":2016,"publication_date":"2016-11-04","ids":{"openalex":"https://openalex.org/W2548765505","doi":"https://doi.org/10.1145/2994551.2994569","mag":"2548765505","pmid":"https://pubmed.ncbi.nlm.nih.gov/30381808"},"language":"en","primary_location":{"id":"doi:10.1145/2994551.2994569","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2994551.2994569","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems CD-ROM","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6205502","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100406079","display_name":"Xinyu Li","orcid":"https://orcid.org/0000-0001-5398-3707"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xinyu Li","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Rutgers University, New Brunswick, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Rutgers University, New Brunswick, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003300255","display_name":"Yanyi Zhang","orcid":"https://orcid.org/0000-0001-5238-1712"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yanyi Zhang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Rutgers University, New Brunswick, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Rutgers University, New Brunswick, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068126329","display_name":"Ivan Marsic","orcid":"https://orcid.org/0000-0002-1033-6865"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ivan Marsic","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Rutgers University, New Brunswick, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Rutgers University, New Brunswick, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081312228","display_name":"Aleksandra Sarcevic","orcid":"https://orcid.org/0000-0003-2126-8527"},"institutions":[{"id":"https://openalex.org/I72816309","display_name":"Drexel University","ror":"https://ror.org/04bdffz58","country_code":"US","type":"education","lineage":["https://openalex.org/I72816309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aleksandra Sarcevic","raw_affiliation_strings":["College of Computing and Informatics, Drexel University, Philadelphia, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computing and Informatics, Drexel University, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I72816309"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002966813","display_name":"Randall S. Burd","orcid":"https://orcid.org/0000-0003-4465-9117"},"institutions":[{"id":"https://openalex.org/I1336742384","display_name":"Children's National","ror":"https://ror.org/03wa2q724","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1336742384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Randall S. Burd","raw_affiliation_strings":["Division of Trauma and Burn Surgery, Children's National Medical Center, Washington, D.C., USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of Trauma and Burn Surgery, Children's National Medical Center, Washington, D.C., USA","institution_ids":["https://openalex.org/I1336742384"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":151,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"2016","issue":null,"first_page":"164","last_page":"175"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9980000257492065,"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":0.9980000257492065,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9858999848365784,"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"}},{"id":"https://openalex.org/T11824","display_name":"Injury Epidemiology and Prevention","score":0.9855999946594238,"subfield":{"id":"https://openalex.org/subfields/2739","display_name":"Public Health, Environmental and Occupational Health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.8213878870010376},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8131431937217712},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7650049328804016},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6721024513244629},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6567214727401733},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.58791583776474},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5091633200645447},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.46428242325782776},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.4402965307235718},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.43812185525894165},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4255245625972748},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41887542605400085},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36676958203315735},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.2241974174976349},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.09535491466522217}],"concepts":[{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.8213878870010376},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8131431937217712},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7650049328804016},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6721024513244629},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6567214727401733},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.58791583776474},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5091633200645447},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.46428242325782776},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.4402965307235718},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.43812185525894165},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4255245625972748},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41887542605400085},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36676958203315735},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.2241974174976349},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.09535491466522217},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1145/2994551.2994569","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2994551.2994569","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems CD-ROM","raw_type":"proceedings-article"},{"id":"pmid:30381808","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/30381808","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":"Proceedings of the ... International Conference on Embedded Networked Sensor Systems. International Conference on Embedded Networked Sensor Systems","raw_type":null},{"id":"pmh:oai:europepmc.org:5151260","is_oa":false,"landing_page_url":"http://europepmc.org/pmc/articles/PMC6205502","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:6205502","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6205502","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proc Int Conf Embed Netw Sens Syst","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:6205502","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6205502","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proc Int Conf Embed Netw Sens Syst","raw_type":"Text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1287356885","display_name":null,"funder_award_id":"R01 LM011834","funder_id":"https://openalex.org/F4320337372","funder_display_name":"U.S. National Library of Medicine"}],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337372","display_name":"U.S. National Library of Medicine","ror":"https://ror.org/0060t0j89"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W46659105","https://openalex.org/W1522301498","https://openalex.org/W1582583989","https://openalex.org/W1686810756","https://openalex.org/W1825675169","https://openalex.org/W1991539813","https://openalex.org/W1997430507","https://openalex.org/W2002640258","https://openalex.org/W2003637680","https://openalex.org/W2016053056","https://openalex.org/W2041742273","https://openalex.org/W2054780155","https://openalex.org/W2060233269","https://openalex.org/W2066536551","https://openalex.org/W2069973845","https://openalex.org/W2070924230","https://openalex.org/W2095705004","https://openalex.org/W2105369247","https://openalex.org/W2109553965","https://openalex.org/W2112796928","https://openalex.org/W2155983176","https://openalex.org/W2156303437","https://openalex.org/W2160815625","https://openalex.org/W2163605009","https://openalex.org/W2168356304","https://openalex.org/W2184188583","https://openalex.org/W2188183693","https://openalex.org/W2210678035","https://openalex.org/W2211722331","https://openalex.org/W2247209766","https://openalex.org/W2269938945","https://openalex.org/W2271840356","https://openalex.org/W2285924575","https://openalex.org/W2296488711","https://openalex.org/W2414118053","https://openalex.org/W2521090836","https://openalex.org/W2526416132","https://openalex.org/W2618530766","https://openalex.org/W2919115771","https://openalex.org/W2964154335","https://openalex.org/W4254373586","https://openalex.org/W6726696498"],"related_works":["https://openalex.org/W3195649134","https://openalex.org/W2281498195","https://openalex.org/W2017526120","https://openalex.org/W2610664080","https://openalex.org/W2188304107","https://openalex.org/W2294565841","https://openalex.org/W2761510556","https://openalex.org/W2892259437","https://openalex.org/W2117913171","https://openalex.org/W2582769230"],"abstract_inverted_index":{"We":[0,17,76,124],"present":[1],"a":[2,12,24,38,61,85],"system":[3,56,79,100],"for":[4,29,68,105,137],"activity":[5,30,58,74,106,138],"recognition":[6,31,59,107,139],"from":[7,46,94,140],"passive":[8],"RFID":[9,21,47,81,92,141],"data":[10,22,48,82,93],"using":[11,37,80],"deep":[13,25,134],"convolutional":[14,26],"neural":[15,27],"network.":[16],"directly":[18],"feed":[19],"the":[20,52,127],"into":[23],"network":[28],"instead":[32],"of":[33,73,91,131],"selecting":[34],"features":[35],"and":[36,108,129],"cascade":[39],"structure":[40],"that":[41,117],"first":[42],"detects":[43],"object":[44],"use":[45],"followed":[49],"by":[50],"predicting":[51],"activity.":[53],"Because":[54],"our":[55,78,132],"treats":[57],"as":[60,115],"multi-class":[62],"classification":[63],"problem,":[64],"it":[65],"is":[66],"scalable":[67],"applications":[69],"with":[70,112],"large":[71],"number":[72],"classes.":[75],"tested":[77],"collected":[83],"in":[84],"trauma":[86,97],"room,":[87],"including":[88],"14":[89],"hours":[90],"16":[95],"actual":[96],"resuscitations.":[98],"Our":[99],"outperformed":[101],"existing":[102],"systems":[103,116],"developed":[104],"achieved":[109],"similar":[110],"performance":[111],"process-phase":[113],"detection":[114],"require":[118],"wearable":[119],"sensors":[120],"or":[121],"manually-generated":[122],"input.":[123],"also":[125],"analyzed":[126],"strengths":[128],"limitations":[130],"current":[133],"learning":[135],"architecture":[136],"data.":[142]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":25},{"year":2022,"cited_by_count":15},{"year":2021,"cited_by_count":16},{"year":2020,"cited_by_count":16},{"year":2019,"cited_by_count":22},{"year":2018,"cited_by_count":19},{"year":2017,"cited_by_count":7}],"updated_date":"2026-07-18T07:39:51.176621","created_date":"2025-10-10T00:00:00"}