{"id":"https://openalex.org/W4317418514","doi":"https://doi.org/10.1109/gcce56475.2022.10014428","title":"Human Activity Recognition with Spiking Neural Network","display_name":"Human Activity Recognition with Spiking Neural Network","publication_year":2022,"publication_date":"2022-10-18","ids":{"openalex":"https://openalex.org/W4317418514","doi":"https://doi.org/10.1109/gcce56475.2022.10014428"},"language":"en","primary_location":{"id":"doi:10.1109/gcce56475.2022.10014428","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce56475.2022.10014428","pdf_url":null,"source":{"id":"https://openalex.org/S4363607800","display_name":"2022 IEEE 11th Global Conference on Consumer Electronics (GCCE)","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 11th Global Conference on Consumer Electronics (GCCE)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5001891621","display_name":"Shang-Chai Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I114150738","display_name":"Fu Jen Catholic University","ror":"https://ror.org/04je98850","country_code":"TW","type":"education","lineage":["https://openalex.org/I114150738"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Shang-Chai Yang","raw_affiliation_strings":["Fu Jen Catholic University,Department of Electrical Engineering,New Taipei City,Taiwan","Department of Electrical Engineering, Fu Jen Catholic University, New Taipei City, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fu Jen Catholic University,Department of Electrical Engineering,New Taipei City,Taiwan","institution_ids":["https://openalex.org/I114150738"]},{"raw_affiliation_string":"Department of Electrical Engineering, Fu Jen Catholic University, New Taipei City, Taiwan","institution_ids":["https://openalex.org/I114150738"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032268276","display_name":"Ming-Lun Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I114150738","display_name":"Fu Jen Catholic University","ror":"https://ror.org/04je98850","country_code":"TW","type":"education","lineage":["https://openalex.org/I114150738"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Ming-Lun Wu","raw_affiliation_strings":["Fu Jen Catholic University,Department of Electrical Engineering,New Taipei City,Taiwan","Department of Electrical Engineering, Fu Jen Catholic University, New Taipei City, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fu Jen Catholic University,Department of Electrical Engineering,New Taipei City,Taiwan","institution_ids":["https://openalex.org/I114150738"]},{"raw_affiliation_string":"Department of Electrical Engineering, Fu Jen Catholic University, New Taipei City, Taiwan","institution_ids":["https://openalex.org/I114150738"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053857348","display_name":"Yuan-Kai Wang","orcid":"https://orcid.org/0000-0002-0676-5886"},"institutions":[{"id":"https://openalex.org/I114150738","display_name":"Fu Jen Catholic University","ror":"https://ror.org/04je98850","country_code":"TW","type":"education","lineage":["https://openalex.org/I114150738"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yuan-Kai Wang","raw_affiliation_strings":["Fu Jen Catholic University,Department of Electrical Engineering,New Taipei City,Taiwan","Department of Electrical Engineering, Fu Jen Catholic University, New Taipei City, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fu Jen Catholic University,Department of Electrical Engineering,New Taipei City,Taiwan","institution_ids":["https://openalex.org/I114150738"]},{"raw_affiliation_string":"Department of Electrical Engineering, Fu Jen Catholic University, New Taipei City, Taiwan","institution_ids":["https://openalex.org/I114150738"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I114150738"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"482","last_page":"483"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9083999991416931,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9083999991416931,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9000999927520752,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.6873437166213989},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.669467568397522},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5482089519500732},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5101637840270996},{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.4875344932079315},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4129776954650879}],"concepts":[{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.6873437166213989},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.669467568397522},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5482089519500732},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5101637840270996},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.4875344932079315},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4129776954650879}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/gcce56475.2022.10014428","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce56475.2022.10014428","pdf_url":null,"source":{"id":"https://openalex.org/S4363607800","display_name":"2022 IEEE 11th Global Conference on Consumer Electronics (GCCE)","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 11th Global Conference on Consumer Electronics (GCCE)","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":4,"referenced_works":["https://openalex.org/W2745933219","https://openalex.org/W2792586906","https://openalex.org/W2984844508","https://openalex.org/W3098559955"],"related_works":["https://openalex.org/W2386387936","https://openalex.org/W3107474891","https://openalex.org/W2033914206","https://openalex.org/W2146076056","https://openalex.org/W2188464267","https://openalex.org/W2922225723","https://openalex.org/W3106494386","https://openalex.org/W2954309397","https://openalex.org/W2885843018","https://openalex.org/W2003715592"],"abstract_inverted_index":{"Most":[0],"of":[1,19,29,60,83,120],"the":[2,17,26,61,73,104,115,127,135],"research":[3],"on":[4,11,48,53,134],"human":[5],"activity":[6,45,109],"recognition":[7,46],"is":[8,100,112,124],"now":[9],"based":[10,47],"deep":[12,20],"learning":[13,21],"methods":[14],"due":[15],"to":[16,71,102,126,144],"rise":[18],"in":[22],"recent":[23],"years.":[24],"As":[25],"third":[27],"generation":[28],"artificial":[30],"neural":[31,34,90],"network,":[32],"spiking":[33,89],"network":[35,91],"provides":[36],"an":[37],"effective":[38],"bionic":[39],"solution":[40],"for":[41,114],"nowadays":[42],"research.":[43],"Human":[44],"event":[49,69],"are":[50,64,132],"challenging":[51],"tasks":[52],"computer":[54],"vision":[55],"community.":[56],"At":[57],"present,":[58],"most":[59],"event-based":[62,105,116,137],"datasets":[63,117,143],"mainly":[65],"produced":[66],"by":[67],"using":[68],"camera":[70],"record":[72],"existing":[74],"frame-based":[75],"image":[76],"datasets,":[77],"therefore":[78],"easily":[79],"contain":[80],"a":[81,88],"lot":[82],"noise.":[84],"In":[85],"this":[86],"paper,":[87],"with":[92,118],"five":[93],"convolutional":[94],"leaky":[95],"integrate":[96],"and":[97,122,141],"fire":[98],"layers":[99],"proposed":[101,113],"train":[103],"dataset.":[106],"The":[107],"background":[108],"filtering":[110],"algorithm":[111],"lots":[119],"noise,":[121],"it":[123],"applied":[125],"data":[128],"augmentation":[129],"method.":[130],"Experiments":[131],"conduced":[133],"three":[136],"datasets:":[138],"DVS-Gesture,":[139],"IITM-DVS":[140],"UCF11-DVS":[142],"show":[145],"that":[146],"our":[147],"approach":[148],"has":[149],"better":[150],"accuracy":[151],"than":[152],"other":[153],"methods.":[154]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}