{"id":"https://openalex.org/W4406980434","doi":"https://doi.org/10.1088/2634-4386/adb070","title":"ReSpike: residual frames-based hybrid spiking neural networks for efficient action recognition","display_name":"ReSpike: residual frames-based hybrid spiking neural networks for efficient action recognition","publication_year":2025,"publication_date":"2025-01-30","ids":{"openalex":"https://openalex.org/W4406980434","doi":"https://doi.org/10.1088/2634-4386/adb070"},"language":"en","primary_location":{"id":"doi:10.1088/2634-4386/adb070","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2634-4386/adb070","pdf_url":null,"source":{"id":"https://openalex.org/S4210212933","display_name":"Neuromorphic Computing and Engineering","issn_l":"2634-4386","issn":["2634-4386"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neuromorphic Computing and Engineering","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1088/2634-4386/adb070","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065874083","display_name":"Shiting Xiao","orcid":"https://orcid.org/0009-0002-7592-9466"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shiting Xiao","raw_affiliation_strings":["Department of Electrical & Computer Engineering, Yale University, New Haven, CT 06520, United States of America"],"raw_orcid":"https://orcid.org/0009-0002-7592-9466","affiliations":[{"raw_affiliation_string":"Department of Electrical & Computer Engineering, Yale University, New Haven, CT 06520, United States of America","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045846687","display_name":"Yuhang Li","orcid":"https://orcid.org/0000-0002-6444-7253"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuhang Li","raw_affiliation_strings":["Department of Electrical & Computer Engineering, Yale University, New Haven, CT 06520, United States of America"],"raw_orcid":"https://orcid.org/0000-0002-6444-7253","affiliations":[{"raw_affiliation_string":"Department of Electrical & Computer Engineering, Yale University, New Haven, CT 06520, United States of America","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082196231","display_name":"Youngeun Kim","orcid":"https://orcid.org/0000-0002-3542-7720"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Youngeun Kim","raw_affiliation_strings":["Department of Electrical & Computer Engineering, Yale University, New Haven, CT 06520, United States of America"],"raw_orcid":"https://orcid.org/0000-0002-3542-7720","affiliations":[{"raw_affiliation_string":"Department of Electrical & Computer Engineering, Yale University, New Haven, CT 06520, United States of America","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022006817","display_name":"Donghyun Lee","orcid":"https://orcid.org/0000-0002-2927-8255"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Donghyun Lee","raw_affiliation_strings":["Department of Electrical & Computer Engineering, Yale University, New Haven, CT 06520, United States of America"],"raw_orcid":"https://orcid.org/0000-0002-2927-8255","affiliations":[{"raw_affiliation_string":"Department of Electrical & Computer Engineering, Yale University, New Haven, CT 06520, United States of America","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050310538","display_name":"Priyadarshini Panda","orcid":"https://orcid.org/0000-0002-4167-6782"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Priyadarshini Panda","raw_affiliation_strings":["Department of Electrical & Computer Engineering, Yale University, New Haven, CT 06520, United States of America"],"raw_orcid":"https://orcid.org/0000-0002-4167-6782","affiliations":[{"raw_affiliation_string":"Department of Electrical & Computer Engineering, Yale University, New Haven, CT 06520, United States of America","institution_ids":["https://openalex.org/I32971472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I32971472"],"apc_list":{"value":2000,"currency":"GBP","value_usd":2453},"apc_paid":{"value":2000,"currency":"GBP","value_usd":2453},"fwci":3.7011,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.92748512,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"5","issue":"1","first_page":"014009","last_page":"014009"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9969000220298767,"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":0.9969000220298767,"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/T10320","display_name":"Neural Networks and Applications","score":0.9857000112533569,"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"}},{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9704999923706055,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.8103945255279541},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.5982220768928528},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5719389319419861},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.5199766755104065},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5168519616127014},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.49838805198669434},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4415643513202667},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1294354796409607},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.04982241988182068}],"concepts":[{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.8103945255279541},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.5982220768928528},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5719389319419861},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.5199766755104065},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5168519616127014},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.49838805198669434},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4415643513202667},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1294354796409607},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.04982241988182068},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"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":2,"locations":[{"id":"doi:10.1088/2634-4386/adb070","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2634-4386/adb070","pdf_url":null,"source":{"id":"https://openalex.org/S4210212933","display_name":"Neuromorphic Computing and Engineering","issn_l":"2634-4386","issn":["2634-4386"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neuromorphic Computing and Engineering","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:d4b8744dbd114655a10ac2602c55413a","is_oa":true,"landing_page_url":"https://doaj.org/article/d4b8744dbd114655a10ac2602c55413a","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":"Neuromorphic Computing and Engineering, Vol 5, Iss 1, p 014009 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1088/2634-4386/adb070","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2634-4386/adb070","pdf_url":null,"source":{"id":"https://openalex.org/S4210212933","display_name":"Neuromorphic Computing and Engineering","issn_l":"2634-4386","issn":["2634-4386"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neuromorphic Computing and Engineering","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4912827401","display_name":null,"funder_award_id":"CAREER Award, Grant #2312366, Grant #2318152","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":82,"referenced_works":["https://openalex.org/W1604973310","https://openalex.org/W2020676607","https://openalex.org/W2159951683","https://openalex.org/W2194775991","https://openalex.org/W2302255633","https://openalex.org/W2513853720","https://openalex.org/W2553594924","https://openalex.org/W2621826044","https://openalex.org/W2783525259","https://openalex.org/W2798878556","https://openalex.org/W2807894615","https://openalex.org/W2892077605","https://openalex.org/W2964031418","https://openalex.org/W2984844508","https://openalex.org/W2990793844","https://openalex.org/W2995256488","https://openalex.org/W3014020978","https://openalex.org/W3097285691","https://openalex.org/W3124546450","https://openalex.org/W3174155187","https://openalex.org/W3196571547","https://openalex.org/W3201424517","https://openalex.org/W3208650852","https://openalex.org/W4206609022","https://openalex.org/W4282837277","https://openalex.org/W4306827030","https://openalex.org/W4367189470","https://openalex.org/W4375850379","https://openalex.org/W4385260104","https://openalex.org/W4386322031","https://openalex.org/W4386699354","https://openalex.org/W4386750938","https://openalex.org/W4391661519","https://openalex.org/W4391818789","https://openalex.org/W4394698802","https://openalex.org/W6600983433","https://openalex.org/W6620707391","https://openalex.org/W6631456553","https://openalex.org/W6649797076","https://openalex.org/W6652671445","https://openalex.org/W6654335291","https://openalex.org/W6658929250","https://openalex.org/W6674914833","https://openalex.org/W6674985822","https://openalex.org/W6676297131","https://openalex.org/W6678616107","https://openalex.org/W6679434410","https://openalex.org/W6684191040","https://openalex.org/W6730169906","https://openalex.org/W6738587995","https://openalex.org/W6739901393","https://openalex.org/W6742667445","https://openalex.org/W6771742384","https://openalex.org/W6775583579","https://openalex.org/W6775671494","https://openalex.org/W6782262041","https://openalex.org/W6784333009","https://openalex.org/W6785277872","https://openalex.org/W6786237780","https://openalex.org/W6790830454","https://openalex.org/W6792155083","https://openalex.org/W6792501799","https://openalex.org/W6794053914","https://openalex.org/W6799061830","https://openalex.org/W6799838802","https://openalex.org/W6809648081","https://openalex.org/W6809859974","https://openalex.org/W6810595431","https://openalex.org/W6811094106","https://openalex.org/W6844652965","https://openalex.org/W6846928370","https://openalex.org/W6847497215","https://openalex.org/W6848569070","https://openalex.org/W6851029726","https://openalex.org/W6851385588","https://openalex.org/W6852107617","https://openalex.org/W6853666707","https://openalex.org/W6854699901","https://openalex.org/W6855893330","https://openalex.org/W6856737197","https://openalex.org/W6862952385","https://openalex.org/W6955071965"],"related_works":["https://openalex.org/W2560215812","https://openalex.org/W2949601986","https://openalex.org/W2788972299","https://openalex.org/W2521347458","https://openalex.org/W2498789492","https://openalex.org/W2729981612","https://openalex.org/W4233449973","https://openalex.org/W1576128429","https://openalex.org/W2952005526","https://openalex.org/W2269464716"],"abstract_inverted_index":{"Abstract":[0],"Spiking":[1],"Neural":[2,15],"Networks":[3,16],"(SNNs)":[4],"have":[5],"emerged":[6],"as":[7,23],"a":[8,61,126],"compelling,":[9],"energy-efficient":[10],"alternative":[11],"to":[12,45,72,135],"traditional":[13],"Artificial":[14],"(ANNs)":[17],"for":[18,112,118,130],"static":[19],"image":[20,24,90],"tasks":[21,76],"such":[22],"classification":[25,34],"and":[26,70,80,99,116,163],"segmentation.":[27],"However,":[28],"in":[29,48],"the":[30,46,66],"more":[31],"complex":[32],"video":[33],"domain,":[35],"SNN-based":[36],"methods":[37],"fall":[38],"considerably":[39],"short":[40],"of":[41,68],"ANN-based":[42],"benchmarks":[43],"due":[44],"challenges":[47],"processing":[49,113],"dense":[50],"frame":[51],"sequences.":[52],"To":[53],"bridge":[54],"this":[55],"gap,":[56],"we":[57,124],"propose":[58,125],"ReSpike":[59,109,140,166],",":[60,93,103],"hybrid":[62,141],"framework":[63],"that":[64],"synergizes":[65],"strengths":[67],"ANNs":[69],"SNNs":[71],"tackle":[73],"action":[74],"recognition":[75],"with":[77,170],"high":[78],"accuracy":[79,158],"low":[81],"energy":[82],"cost.":[83],"By":[84],"partitioning":[85],"film":[86],"clips":[87],"into":[88],"RGB":[89],"Key":[91],"Frames":[92,102],"which":[94,104],"primarily":[95],"capture":[96],"spatial":[97,114],"information,":[98],"event-like":[100],"Residual":[101],"emphasize":[105],"temporal":[106,120],"dynamics":[107],"cues,":[108],"leverages":[110],"ANN":[111,172],"features":[115],"SNN":[117,137],"modeling":[119],"features.":[121],"In":[122],"addition,":[123],"multi-scale":[127],"cross-attention":[128],"mechanism":[129],"effective":[131],"feature":[132],"fusion.":[133],"Compared":[134],"state-of-the-art":[136],"baselines,":[138],"our":[139],"architecture":[142],"demonstrates":[143],"significant":[144],"performance":[145,169],"improvements":[146],"(e.g.":[147],"<mml:math":[148],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[149],"overflow=\"scroll\">":[150],"<mml:mrow>":[151],"<mml:mo>&gt;</mml:mo>":[152],"</mml:mrow>":[153],"</mml:math>":[154],"30":[155],"%":[156],"absolute":[157],"improvement":[159],"on":[160],"HMDB-51,":[161],"UCF-101,":[162],"Kinetics-400).":[164],"Furthermore,":[165],"achieves":[167],"comparable":[168],"prior":[171],"approaches":[173],"while":[174],"bringing":[175],"better":[176],"accuracy-energy":[177],"tradeoff.":[178],"Code":[179],"is":[180],"shared":[181],"at":[182],"https://github.com/Intelligent-Computing-Lab-Yale/ReSpike":[183],".":[184]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":4}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}