{"id":"https://openalex.org/W3172961237","doi":"https://doi.org/10.1109/access.2021.3085708","title":"Making Sense of Neuromorphic Event Data for Human Action Recognition","display_name":"Making Sense of Neuromorphic Event Data for Human Action Recognition","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3172961237","doi":"https://doi.org/10.1109/access.2021.3085708","mag":"3172961237"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3085708","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3085708","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09446050.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09446050.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087176168","display_name":"Salah Al-Obaidi","orcid":"https://orcid.org/0000-0003-4521-7193"},"institutions":[{"id":"https://openalex.org/I91136226","display_name":"University of Sheffield","ror":"https://ror.org/05krs5044","country_code":"GB","type":"education","lineage":["https://openalex.org/I91136226"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Salah Al-Obaidi","raw_affiliation_strings":["The University of Sheffield, Sheffield, U.K"],"raw_orcid":"https://orcid.org/0000-0003-4521-7193","affiliations":[{"raw_affiliation_string":"The University of Sheffield, Sheffield, U.K","institution_ids":["https://openalex.org/I91136226"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003821051","display_name":"Hiba Al-Khafaji","orcid":null},"institutions":[{"id":"https://openalex.org/I91136226","display_name":"University of Sheffield","ror":"https://ror.org/05krs5044","country_code":"GB","type":"education","lineage":["https://openalex.org/I91136226"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Hiba Al-Khafaji","raw_affiliation_strings":["The University of Sheffield, Sheffield, U.K"],"raw_orcid":"https://orcid.org/0000-0002-4977-9284","affiliations":[{"raw_affiliation_string":"The University of Sheffield, Sheffield, U.K","institution_ids":["https://openalex.org/I91136226"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035952586","display_name":"Charith Abhayaratne","orcid":"https://orcid.org/0000-0002-2799-7395"},"institutions":[{"id":"https://openalex.org/I91136226","display_name":"University of Sheffield","ror":"https://ror.org/05krs5044","country_code":"GB","type":"education","lineage":["https://openalex.org/I91136226"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Charith Abhayaratne","raw_affiliation_strings":["The University of Sheffield, Sheffield, U.K"],"raw_orcid":"https://orcid.org/0000-0002-2799-7395","affiliations":[{"raw_affiliation_string":"The University of Sheffield, Sheffield, U.K","institution_ids":["https://openalex.org/I91136226"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I91136226"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.3768,"has_fulltext":true,"cited_by_count":22,"citation_normalized_percentile":{"value":0.80623076,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"9","issue":null,"first_page":"82686","last_page":"82700"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9973999857902527,"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"}},{"id":"https://openalex.org/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9972000122070312,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/neuromorphic-engineering","display_name":"Neuromorphic engineering","score":0.8678346872329712},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8085006475448608},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6759265065193176},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6101125478744507},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.586012065410614},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4965513348579407},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.4734591841697693},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4656655788421631},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.4300987422466278},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3639894723892212},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.22800171375274658}],"concepts":[{"id":"https://openalex.org/C151927369","wikidata":"https://www.wikidata.org/wiki/Q1981312","display_name":"Neuromorphic engineering","level":3,"score":0.8678346872329712},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8085006475448608},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6759265065193176},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6101125478744507},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.586012065410614},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4965513348579407},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.4734591841697693},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4656655788421631},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.4300987422466278},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3639894723892212},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.22800171375274658},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/access.2021.3085708","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3085708","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09446050.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:eprints.whiterose.ac.uk:175216","is_oa":true,"landing_page_url":null,"pdf_url":"https://eprints.whiterose.ac.uk/175216/1/09446050.pdf","source":{"id":"https://openalex.org/S4306400854","display_name":"White Rose Research Online (University of Leeds, The University of Sheffield, University of York)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2800616092","host_organization_name":"White Rose University Consortium","host_organization_lineage":["https://openalex.org/I2800616092"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Article"},{"id":"pmh:oai:doaj.org/article:26a3f2dc17dd409e9550ff7e5d065665","is_oa":true,"landing_page_url":"https://doaj.org/article/26a3f2dc17dd409e9550ff7e5d065665","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":"IEEE Access, Vol 9, Pp 82686-82700 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3085708","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3085708","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09446050.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7799999713897705,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320311039","display_name":"Ministry of Higher Education and Scientific Research","ror":"https://ror.org/00kab6t91"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3172961237.pdf","grobid_xml":"https://content.openalex.org/works/W3172961237.grobid-xml"},"referenced_works_count":69,"referenced_works":["https://openalex.org/W206948248","https://openalex.org/W854522590","https://openalex.org/W1522734439","https://openalex.org/W1769907550","https://openalex.org/W1944615693","https://openalex.org/W1981781955","https://openalex.org/W2006487439","https://openalex.org/W2016574277","https://openalex.org/W2018904782","https://openalex.org/W2034328688","https://openalex.org/W2065778157","https://openalex.org/W2100916003","https://openalex.org/W2124929138","https://openalex.org/W2126579184","https://openalex.org/W2128754010","https://openalex.org/W2144187604","https://openalex.org/W2155268664","https://openalex.org/W2156303437","https://openalex.org/W2156640153","https://openalex.org/W2166333243","https://openalex.org/W2322020277","https://openalex.org/W2411086162","https://openalex.org/W2481030481","https://openalex.org/W2506323698","https://openalex.org/W2507540959","https://openalex.org/W2510185399","https://openalex.org/W2537595437","https://openalex.org/W2567239141","https://openalex.org/W2587802086","https://openalex.org/W2613967272","https://openalex.org/W2745933219","https://openalex.org/W2755006634","https://openalex.org/W2774716830","https://openalex.org/W2782776028","https://openalex.org/W2792586906","https://openalex.org/W2805391940","https://openalex.org/W2891530223","https://openalex.org/W2899000831","https://openalex.org/W2912374160","https://openalex.org/W2922107638","https://openalex.org/W2925837493","https://openalex.org/W2937345436","https://openalex.org/W2940407355","https://openalex.org/W2951417227","https://openalex.org/W2963076818","https://openalex.org/W2964273528","https://openalex.org/W2969224356","https://openalex.org/W2979969178","https://openalex.org/W2981539886","https://openalex.org/W3034681945","https://openalex.org/W3087591564","https://openalex.org/W3088250895","https://openalex.org/W3089954304","https://openalex.org/W3098559955","https://openalex.org/W3109931275","https://openalex.org/W3122048951","https://openalex.org/W3122190729","https://openalex.org/W3133758660","https://openalex.org/W4226051885","https://openalex.org/W4249279051","https://openalex.org/W4303579812","https://openalex.org/W6682864246","https://openalex.org/W6747795875","https://openalex.org/W6754595668","https://openalex.org/W6755494875","https://openalex.org/W6778791504","https://openalex.org/W6783578821","https://openalex.org/W6788818291","https://openalex.org/W6810879400"],"related_works":["https://openalex.org/W2986579802","https://openalex.org/W4389237622","https://openalex.org/W3108691306","https://openalex.org/W4385753159","https://openalex.org/W4200152843","https://openalex.org/W4214914769","https://openalex.org/W4387251107","https://openalex.org/W2166309310","https://openalex.org/W4317717548","https://openalex.org/W4297621941"],"abstract_inverted_index":{"Neuromorphic":[0],"vision":[1,48,226],"sensors":[2],"provide":[3,32],"low":[4,139],"power":[5],"sensing":[6,18],"and":[7,90,148,169,191,196,211],"capture":[8],"salient":[9],"spatial-temporal":[10],"events.":[11],"The":[12,64,100,158,172],"majority":[13],"of":[14,74,87,108,131,133,165,182],"the":[15,29,46,80,85,96,113,122,129,134,177,217],"existing":[16,178],"neuromorphic":[17,47,225],"work":[19],"focus":[20],"on":[21,69,224],"object":[22],"detection.":[23],"However,":[24],"since":[25],"they":[26,31],"only":[27],"record":[28],"events,":[30],"an":[33],"efficient":[34],"signal":[35],"domain":[36],"for":[37,55,78,193,205,216,220],"privacy":[38],"aware":[39],"surveillance":[40],"tasks.":[41],"This":[42,200],"paper":[43,201],"explores":[44],"how":[45],"sensor":[49,227],"data":[50],"streams":[51],"can":[52],"be":[53],"analysed":[54],"human":[56,98,183,221],"action":[57,184,222],"recognition,":[58],"which":[59,213],"is":[60,67],"a":[61,75,106,117],"challenging":[62],"application.":[63],"proposed":[65,159,173],"method":[66,160,174],"based":[68],"handcrafted":[70,88],"features.":[71],"It":[72],"consists":[73],"pre-processing":[76],"step":[77],"removing":[79],"noisy":[81],"events":[82,115],"followed":[83],"by":[84,127,188],"extraction":[86],"local":[89,101],"global":[91,123],"feature":[92,156],"vectors":[93],"corresponding":[94],"to":[95],"underlying":[97],"action.":[99],"features":[102,124],"are":[103,125,152,214],"extracted":[104,126],"considering":[105,128],"set":[107],"high-order":[109],"descriptive":[110],"statistics":[111],"from":[112],"spatio-temporal":[114],"in":[116,180],"time":[118,219],"window":[119],"slice,":[120],"while":[121],"frequencies":[130],"occurrences":[132],"temporal":[135],"event":[136],"sequences.":[137],"Then,":[138],"complexity":[140],"classifiers,":[141],"such":[142],"as,":[143],"support":[144],"vector":[145],"machines":[146],"(SVM)":[147],"K-Nearest":[149],"Neighbours":[150],"(KNNs),":[151],"trained":[153],"using":[154],"these":[155],"vectors.":[157],"evaluation":[161],"uses":[162],"three":[163,206],"groups":[164],"datasets:":[166,208],"Emulator-based,":[167],"re-recording-based":[168],"native":[170],"NVS-based.":[171],"has":[175],"outperformed":[176],"methods":[179],"terms":[181],"recognition":[185,223],"accuracy":[186],"rates":[187],"0.54%,":[189],"19.3%,":[190],"25.61%":[192],"E-KTH,":[194],"E-UCF11":[195],"E-HMDB51":[197],"datasets,":[198],"respectively.":[199],"also":[202],"reports":[203],"results":[204],"further":[207],"E-UCF50,":[209],"R-UCF50,":[210],"N-Actions,":[212],"reported":[215],"first":[218],"domain.":[228]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}