{"id":"https://openalex.org/W4383066328","doi":"https://doi.org/10.1109/icra48891.2023.10160551","title":"Adaptive-SpikeNet: Event-based Optical Flow Estimation using Spiking Neural Networks with Learnable Neuronal Dynamics","display_name":"Adaptive-SpikeNet: Event-based Optical Flow Estimation using Spiking Neural Networks with Learnable Neuronal Dynamics","publication_year":2023,"publication_date":"2023-05-29","ids":{"openalex":"https://openalex.org/W4383066328","doi":"https://doi.org/10.1109/icra48891.2023.10160551"},"language":"en","primary_location":{"id":"doi:10.1109/icra48891.2023.10160551","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48891.2023.10160551","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Robotics and Automation (ICRA)","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/A5008650954","display_name":"Adarsh Kumar Kosta","orcid":"https://orcid.org/0000-0001-6377-6701"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Adarsh Kumar Kosta","raw_affiliation_strings":["Purdue University,West Lafayette,USA,IN 47907"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University,West Lafayette,USA,IN 47907","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031161187","display_name":"Kaushik Roy","orcid":"https://orcid.org/0000-0002-0735-9695"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kaushik Roy","raw_affiliation_strings":["Purdue University,West Lafayette,USA,IN 47907"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University,West Lafayette,USA,IN 47907","institution_ids":["https://openalex.org/I219193219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.436,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.93108814,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"6021","last_page":"6027"},"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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9987000226974487,"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/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9979000091552734,"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":0.8422123193740845},{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.8272634744644165},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5810012817382812},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5582199692726135},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5392571687698364},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.46743741631507874},{"id":"https://openalex.org/keywords/asynchronous-communication","display_name":"Asynchronous communication","score":0.4348711669445038},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3905158042907715},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.10708305239677429}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8422123193740845},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.8272634744644165},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5810012817382812},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5582199692726135},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5392571687698364},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.46743741631507874},{"id":"https://openalex.org/C151319957","wikidata":"https://www.wikidata.org/wiki/Q752739","display_name":"Asynchronous communication","level":2,"score":0.4348711669445038},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3905158042907715},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.10708305239677429},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"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/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra48891.2023.10160551","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48891.2023.10160551","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.8299999833106995}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W206948248","https://openalex.org/W603908379","https://openalex.org/W1522301498","https://openalex.org/W1604973310","https://openalex.org/W1901129140","https://openalex.org/W1975697167","https://openalex.org/W1999085092","https://openalex.org/W2007016603","https://openalex.org/W2016574277","https://openalex.org/W2076964542","https://openalex.org/W2092252351","https://openalex.org/W2112287655","https://openalex.org/W2150355110","https://openalex.org/W2153525021","https://openalex.org/W2155302366","https://openalex.org/W2507953016","https://openalex.org/W2734448826","https://openalex.org/W2745933219","https://openalex.org/W2775079417","https://openalex.org/W2783525259","https://openalex.org/W2785582094","https://openalex.org/W2788172931","https://openalex.org/W2883294120","https://openalex.org/W2899000831","https://openalex.org/W2904275768","https://openalex.org/W2962804204","https://openalex.org/W2968243907","https://openalex.org/W3046044791","https://openalex.org/W3092083701","https://openalex.org/W3097980825","https://openalex.org/W3102040318","https://openalex.org/W3105213754","https://openalex.org/W3106188738","https://openalex.org/W3109192943","https://openalex.org/W3129515718","https://openalex.org/W3138915575","https://openalex.org/W3139658937","https://openalex.org/W3177222833","https://openalex.org/W4205499887","https://openalex.org/W4205982568","https://openalex.org/W4287126156","https://openalex.org/W6618372016","https://openalex.org/W6631190155","https://openalex.org/W6639824700","https://openalex.org/W6755494875","https://openalex.org/W6781541960","https://openalex.org/W6785213311","https://openalex.org/W6840495885"],"related_works":["https://openalex.org/W2116677773","https://openalex.org/W2155261584","https://openalex.org/W2584231425","https://openalex.org/W2042919702","https://openalex.org/W2150611273","https://openalex.org/W4207086172","https://openalex.org/W4225981436","https://openalex.org/W2156185805","https://openalex.org/W3126544799","https://openalex.org/W2770353918"],"abstract_inverted_index":{"Event-based":[0],"cameras":[1],"have":[2],"recently":[3],"shown":[4],"great":[5],"potential":[6],"for":[7,86,153,220],"high-speed":[8],"motion":[9],"estimation":[10,159],"owing":[11],"to":[12,15,94,106,109,128,142,189,257],"their":[13,26,224],"ability":[14],"capture":[16],"temporally":[17],"rich":[18],"information":[19,53,72],"asynchronously.":[20],"Spiking":[21],"Neural":[22,98],"Networks":[23,99],"(SNNs),":[24],"with":[25,124],"neuro-inspired":[27],"event-driven":[28],"processing":[29],"can":[30,46],"efficiently":[31],"handle":[32],"such":[33,39],"asynchronous":[34],"data,":[35],"while":[36,73,250],"neuron":[37,68],"models":[38,197,203,222],"as":[40],"the":[41,50,56,67,130,154,161,168,216,227,258],"leaky-integrate":[42],"and":[43,167,198,223,244],"fire":[44],"(LIF)":[45],"keep":[47],"track":[48],"of":[49,156,180,218,231],"quintessential":[51],"timing":[52],"contained":[54],"in":[55,66,183,238],"inputs.":[57],"SNNs":[58,83,103,146,219,234],"achieve":[59],"this":[60],"by":[61],"maintaining":[62],"a":[63],"dynamic":[64],"state":[65],"memory,":[69],"retaining":[70],"important":[71],"forgetting":[74],"redundant":[75],"data":[76],"over":[77],"time.":[78],"Thus,":[79],"we":[80,118],"posit":[81],"that":[82,116,200],"would":[84],"allow":[85],"better":[87],"performance":[88],"on":[89,160,173],"sequential":[90],"regression":[91],"tasks":[92],"compared":[93,188,256],"similarly":[95,206],"sized":[96,207],"Analog":[97],"(ANNs).":[100],"However,":[101],"deep":[102,145],"are":[104],"difficult":[105],"train":[107,143],"due":[108],"vanishing":[110,132],"spikes":[111],"at":[112,226],"later":[113],"layers.":[114],"To":[115],"effect,":[117],"propose":[119],"an":[120,177],"adaptive":[121],"fully-spiking":[122],"framework":[123],"learnable":[125],"neuronal":[126],"dynamics":[127],"alleviate":[129],"spike":[131],"problem.":[133],"We":[134,149,192],"utilize":[135],"surrogate":[136],"gradient-based":[137],"backpropagation":[138],"through":[139],"time":[140],"(BPTT)":[141],"our":[144,151,201,233],"from":[147],"scratch.":[148],"validate":[150],"approach":[152],"task":[155],"optical":[157],"flow":[158],"Multi-Vehicle":[162],"Stereo":[163],"Event-Camera":[164],"(MVSEC)":[165],"dataset":[166],"DSEC-Flow":[169],"dataset.":[170],"Our":[171],"experiments":[172],"these":[174],"datasets":[175],"show":[176],"average":[178,184],"reduction":[179],"\u223c":[181,252],"13%":[182],"endpoint":[185],"error":[186],"(AEE)":[187],"state-of-the-art":[190,259],"ANNs.":[191],"also":[193],"explore":[194],"several":[195],"down-scaled":[196],"observe":[199],"SNN":[202],"consistently":[204],"outperform":[205],"ANNs":[208],"offering":[209],"\u223c10%-16%":[210],"lower":[211,254],"AEE.":[212],"These":[213],"results":[214],"demonstrate":[215],"importance":[217],"smaller":[221],"suitability":[225],"edge.":[228],"In":[229],"terms":[230],"efficiency,":[232],"offer":[235],"substantial":[236],"savings":[237],"network":[239],"parameters":[240],"(\u223c":[241,247],"48.3":[242],"\u00d7)":[243,249],"computational":[245],"energy":[246],"10.2":[248],"attaining":[251],"10%":[253],"EPE":[255],"ANN":[260],"implementations.":[261]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
