{"id":"https://openalex.org/W4416252158","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227338","title":"An Effective GANs-Based Method for High-Information-Value Multimodal Wearable Sensor Data Synthesis","display_name":"An Effective GANs-Based Method for High-Information-Value Multimodal Wearable Sensor Data Synthesis","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416252158","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227338"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11227338","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227338","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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":"https://openalex.org/A5007472373","display_name":"Jiwei Wang","orcid":"https://orcid.org/0000-0003-0593-1843"},"institutions":[{"id":"https://openalex.org/I4210142748","display_name":"Shandong Academy of Sciences","ror":"https://ror.org/04y8d6y55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiwei Wang","raw_affiliation_strings":["Qilu University of Technology(Shandong Academy of Sciences),Shandong Artificial Intelligence Institute,Jinan,China"],"affiliations":[{"raw_affiliation_string":"Qilu University of Technology(Shandong Academy of Sciences),Shandong Artificial Intelligence Institute,Jinan,China","institution_ids":["https://openalex.org/I4210142748"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048871276","display_name":"Yang Gu","orcid":"https://orcid.org/0000-0001-8572-2907"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Gu","raw_affiliation_strings":["Chinese Academy of Sciences,Institute of Computing Technology,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences,Institute of Computing Technology,Beijing,China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055228235","display_name":"Shuwang Zhou","orcid":"https://orcid.org/0000-0003-3471-7563"},"institutions":[{"id":"https://openalex.org/I4210142748","display_name":"Shandong Academy of Sciences","ror":"https://ror.org/04y8d6y55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuwang Zhou","raw_affiliation_strings":["Qilu University of Technology(Shandong Academy of Sciences),Shandong Artificial Intelligence Institute,Jinan,China"],"affiliations":[{"raw_affiliation_string":"Qilu University of Technology(Shandong Academy of Sciences),Shandong Artificial Intelligence Institute,Jinan,China","institution_ids":["https://openalex.org/I4210142748"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100603521","display_name":"Zhaoyang Liu","orcid":"https://orcid.org/0000-0002-3992-701X"},"institutions":[{"id":"https://openalex.org/I4210142748","display_name":"Shandong Academy of Sciences","ror":"https://ror.org/04y8d6y55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaoyang Liu","raw_affiliation_strings":["Qilu University of Technology(Shandong Academy of Sciences),Shandong Artificial Intelligence Institute,Jinan,China"],"affiliations":[{"raw_affiliation_string":"Qilu University of Technology(Shandong Academy of Sciences),Shandong Artificial Intelligence Institute,Jinan,China","institution_ids":["https://openalex.org/I4210142748"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5007472373"],"corresponding_institution_ids":["https://openalex.org/I4210142748"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.34609642,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.4117000102996826,"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":0.4117000102996826,"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":0.08919999748468399,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.049800001084804535,"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/field","display_name":"Field (mathematics)","score":0.5547999739646912},{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.5536999702453613},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.46630001068115234},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.40459999442100525},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.3928999900817871},{"id":"https://openalex.org/keywords/data-collection","display_name":"Data collection","score":0.3702000081539154},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.3513000011444092}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6988000273704529},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5547999739646912},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.5536999702453613},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4860999882221222},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4722999930381775},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.46630001068115234},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.40459999442100525},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3928999900817871},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.3702000081539154},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.3513000011444092},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.3343000113964081},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3337000012397766},{"id":"https://openalex.org/C163985040","wikidata":"https://www.wikidata.org/wiki/Q1172399","display_name":"Data acquisition","level":2,"score":0.3337000012397766},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.2962999939918518},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.28619998693466187},{"id":"https://openalex.org/C115575686","wikidata":"https://www.wikidata.org/wiki/Q18822403","display_name":"Soft sensor","level":3,"score":0.28349998593330383},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.27639999985694885},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.26840001344680786},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.26179999113082886}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11227338","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227338","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320328720","display_name":"Qilu University of Technology","ror":"https://ror.org/04hyzq608"},{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1580375566","https://openalex.org/W2387843324","https://openalex.org/W2584755547","https://openalex.org/W2736191430","https://openalex.org/W2897551993","https://openalex.org/W2962770929","https://openalex.org/W2962793481","https://openalex.org/W2972570007","https://openalex.org/W3028846921","https://openalex.org/W3039434791","https://openalex.org/W3084542156","https://openalex.org/W3086632078","https://openalex.org/W3087753247","https://openalex.org/W3131883848","https://openalex.org/W3211122550","https://openalex.org/W4306394127","https://openalex.org/W4319594598","https://openalex.org/W4380789340","https://openalex.org/W4385493696","https://openalex.org/W4390937897","https://openalex.org/W4391759515","https://openalex.org/W4391843574","https://openalex.org/W4394873395","https://openalex.org/W4394932852","https://openalex.org/W4400438459","https://openalex.org/W4404193058","https://openalex.org/W4404955303","https://openalex.org/W4406114736","https://openalex.org/W4411403377"],"related_works":[],"abstract_inverted_index":{"In":[0],"the":[1,20,36,50,88,99,105,125,129,143],"field":[2],"of":[3,24,38,42,98],"Human":[4],"Activity":[5],"Recognition":[6],"(HAR),":[7],"current":[8],"GANs-based":[9,67],"approaches":[10],"for":[11,19,72,156],"sensor":[12,68,150],"data":[13,25,43,69,75,100],"synthesis":[14,70],"frequently":[15],"fail":[16,55],"to":[17,35,56,59,92,108],"account":[18],"varying":[21],"informational":[22,47],"significance":[23],"samples,":[26],"often":[27],"treating":[28],"them":[29],"with":[30,45,77],"uniform":[31],"importance.":[32],"This":[33,62],"leads":[34],"generation":[37],"a":[39,94],"substantial":[40],"number":[41],"samples":[44,76],"limited":[46],"utility":[48],"by":[49,115],"trained":[51],"generator,":[52],"which":[53,152],"ultimately":[54],"contribute":[57],"meaningfully":[58],"HAR":[60,159],"tasks.":[61],"paper":[63],"introduces":[64],"an":[65],"effective":[66],"method":[71,127,145],"generating":[73],"more":[74,95,154],"high":[78],"information":[79],"value.":[80],"Firstly,":[81],"we":[82,103,123],"incorporate":[83],"active":[84],"learning":[85,97],"mechanisms":[86],"into":[87],"adversarial":[89],"training":[90,157],"architecture":[91],"guide":[93],"comprehensive":[96],"distribution.":[101],"Secondly,":[102],"enhance":[104],"model\u2019s":[106],"ability":[107],"learn":[109],"temporal,":[110],"spatial,":[111],"and":[112,119,135],"spatial-temporal":[113],"features":[114],"combining":[116],"convolutional,":[117],"recurrent,":[118],"self-attention":[120],"modules.":[121],"Thirdly,":[122],"validate":[124],"proposed":[126,144],"on":[128],"public":[130],"dataset":[131],"using":[132],"both":[133],"quantitative":[134],"qualitative":[136],"metrics.":[137],"The":[138],"experimental":[139],"results":[140],"demonstrate":[141],"that":[142],"can":[146],"synthesize":[147],"high-information-value":[148],"multimodal":[149],"data,":[151],"are":[153],"valuable":[155],"downstream":[158],"models.":[160]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-11-14T00:00:00"}
