{"id":"https://openalex.org/W4409759888","doi":"https://doi.org/10.1109/csicc65765.2025.10967410","title":"Optimized Multi-Label Human Activity Recognition with Focal Loss and Attention-Enhanced LSTM Networks","display_name":"Optimized Multi-Label Human Activity Recognition with Focal Loss and Attention-Enhanced LSTM Networks","publication_year":2025,"publication_date":"2025-02-05","ids":{"openalex":"https://openalex.org/W4409759888","doi":"https://doi.org/10.1109/csicc65765.2025.10967410"},"language":"en","primary_location":{"id":"doi:10.1109/csicc65765.2025.10967410","is_oa":false,"landing_page_url":"https://doi.org/10.1109/csicc65765.2025.10967410","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 29th International Computer Conference, Computer Society of Iran (CSICC)","raw_type":"proceedings-article"},"type":"article","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":null,"display_name":"Ali Zohrevand","orcid":null},"institutions":[{"id":"https://openalex.org/I23946033","display_name":"University of Tehran","ror":"https://ror.org/05vf56z40","country_code":"IR","type":"education","lineage":["https://openalex.org/I23946033"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Ali Zohrevand","raw_affiliation_strings":["School of Mathematics, Statistics and Computer Science, College of Science, University of Tehran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics, Statistics and Computer Science, College of Science, University of Tehran","institution_ids":["https://openalex.org/I23946033"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026428383","display_name":"Sayeh Mirzaei","orcid":"https://orcid.org/0000-0003-1174-2280"},"institutions":[{"id":"https://openalex.org/I23946033","display_name":"University of Tehran","ror":"https://ror.org/05vf56z40","country_code":"IR","type":"education","lineage":["https://openalex.org/I23946033"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Sayeh Mirzaei","raw_affiliation_strings":["School of Engineering Science, College of Engineering, University of Tehran,Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Engineering Science, College of Engineering, University of Tehran,Iran","institution_ids":["https://openalex.org/I23946033"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072704310","display_name":"Hedieh Sajedi","orcid":"https://orcid.org/0000-0003-4782-9222"},"institutions":[{"id":"https://openalex.org/I23946033","display_name":"University of Tehran","ror":"https://ror.org/05vf56z40","country_code":"IR","type":"education","lineage":["https://openalex.org/I23946033"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Hedieh Sajedi","raw_affiliation_strings":["School of Mathematics, Statistics and Computer Science, College of Science, University of Tehran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics, Statistics and Computer Science, College of Science, University of Tehran","institution_ids":["https://openalex.org/I23946033"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I23946033"],"apc_list":null,"apc_paid":null,"fwci":0.8823,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.72718222,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9998000264167786,"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":0.9998000264167786,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.988099992275238,"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":0.9879999756813049,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7105286717414856},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4953669309616089}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7105286717414856},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4953669309616089}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/csicc65765.2025.10967410","is_oa":false,"landing_page_url":"https://doi.org/10.1109/csicc65765.2025.10967410","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 29th International Computer Conference, Computer Society of Iran (CSICC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W2002261403","https://openalex.org/W2054780155","https://openalex.org/W2064675550","https://openalex.org/W2073401630","https://openalex.org/W2133564696","https://openalex.org/W2247209766","https://openalex.org/W2270470215","https://openalex.org/W2730215775","https://openalex.org/W2736191430","https://openalex.org/W2767979715","https://openalex.org/W2795342689","https://openalex.org/W2963373106","https://openalex.org/W3164845984","https://openalex.org/W4385245566","https://openalex.org/W4389833669","https://openalex.org/W4392001995","https://openalex.org/W4399208015","https://openalex.org/W6605479355","https://openalex.org/W6679434410","https://openalex.org/W6704286305","https://openalex.org/W6739901393","https://openalex.org/W6742348326"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Recognizing":[0],"human":[1,46,78,160],"activity":[2,62,79],"using":[3],"artificial":[4],"intelligence":[5],"and":[6,21,35,41,59,71,91,113,117,148,158],"deep":[7,48,69,137],"learning":[8,70,149],"methods":[9,108],"has":[10],"become":[11],"increasingly":[12],"important":[13],"in":[14,74,85,115,144],"various":[15],"fields,":[16],"including":[17],"medicine,":[18],"sports,":[19],"security,":[20],"wearable":[22],"technology.":[23],"With":[24],"the":[25,36,57,75,86],"rise":[26],"of":[27,45,61,77,88],"data":[28,90,102,147],"collection":[29],"tools":[30],"that":[31],"utilize":[32],"multidimensional":[33,146],"sensors":[34],"growing":[37],"need":[38],"for":[39,156],"faster":[40],"more":[42],"accurate":[43],"analysis":[44,94],"behaviors,":[47],"neural":[49,72,138],"networks":[50,73],"can":[51],"potentially":[52],"improve":[53],"traditional":[54],"approaches,":[55],"enhancing":[56],"accuracy":[58,112],"efficiency":[60,114],"detection":[63],"systems.":[64],"This":[65],"research,":[66],"which":[67,121],"leverages":[68],"arena":[76],"detection,":[80],"plays":[81],"a":[82],"significant":[83],"role":[84],"advancement":[87],"sensor":[89],"time":[92,100],"series":[93,101],"models.":[95,140],"Previous":[96],"studies":[97],"often":[98],"converted":[99],"into":[103],"structured":[104],"formats;":[105],"however,":[106],"these":[107],"mainly":[109],"struggled":[110],"with":[111],"representing":[116],"analyzing":[118],"complex":[119,150],"features,":[120,151],"limited":[122],"their":[123],"practical":[124],"applications.":[125],"The":[126],"current":[127],"research":[128],"aims":[129],"to":[130],"address":[131],"this":[132],"gap":[133],"by":[134],"focusing":[135],"on":[136],"network":[139],"These":[141],"models":[142],"excel":[143],"processing":[145],"making":[152],"them":[153],"better":[154],"suited":[155],"recognizing":[157],"classifying":[159],"behaviors.":[161]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
