{"id":"https://openalex.org/W4306827030","doi":"https://doi.org/10.1088/2634-4386/ac9b86","title":"Beyond classification: directly training spiking neural networks for semantic segmentation","display_name":"Beyond classification: directly training spiking neural networks for semantic segmentation","publication_year":2022,"publication_date":"2022-10-19","ids":{"openalex":"https://openalex.org/W4306827030","doi":"https://doi.org/10.1088/2634-4386/ac9b86"},"language":"en","primary_location":{"id":"doi:10.1088/2634-4386/ac9b86","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2634-4386/ac9b86","pdf_url":"https://iopscience.iop.org/article/10.1088/2634-4386/ac9b86/pdf","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://iopscience.iop.org/article/10.1088/2634-4386/ac9b86/pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","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":true,"raw_author_name":"Youngeun Kim","raw_affiliation_strings":["Department of Electrical Engineering, Yale University, New Haven, CT, United States of America"],"raw_orcid":"https://orcid.org/0000-0002-3542-7720","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Yale University, New Haven, CT, United States of America","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017226069","display_name":"Joshua Chough","orcid":null},"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":"Joshua Chough","raw_affiliation_strings":["Department of Electrical Engineering, Yale University, New Haven, CT, United States of America"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Yale University, New Haven, CT, 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 Engineering, Yale University, New Haven, CT, United States of America"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Yale University, New Haven, CT, United States of America","institution_ids":["https://openalex.org/I32971472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5082196231"],"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":5.0665,"has_fulltext":false,"cited_by_count":79,"citation_normalized_percentile":{"value":0.9664884,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"2","issue":"4","first_page":"044015","last_page":"044015"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":1.0,"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":1.0,"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/T10581","display_name":"Neural dynamics and brain function","score":0.9970999956130981,"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":0.994700014591217,"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/computer-science","display_name":"Computer science","score":0.8417028188705444},{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.7588727474212646},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.6536435484886169},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6376160383224487},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6344882249832153},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5077808499336243},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4867589473724365},{"id":"https://openalex.org/keywords/pascal","display_name":"Pascal (unit)","score":0.47799649834632874},{"id":"https://openalex.org/keywords/stochastic-gradient-descent","display_name":"Stochastic gradient descent","score":0.4499630630016327},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4332755506038666},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4097442626953125}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8417028188705444},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.7588727474212646},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.6536435484886169},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6376160383224487},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6344882249832153},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5077808499336243},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4867589473724365},{"id":"https://openalex.org/C75608658","wikidata":"https://www.wikidata.org/wiki/Q44395","display_name":"Pascal (unit)","level":2,"score":0.47799649834632874},{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.4499630630016327},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4332755506038666},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4097442626953125},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1088/2634-4386/ac9b86","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2634-4386/ac9b86","pdf_url":"https://iopscience.iop.org/article/10.1088/2634-4386/ac9b86/pdf","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"}],"best_oa_location":{"id":"doi:10.1088/2634-4386/ac9b86","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2634-4386/ac9b86","pdf_url":"https://iopscience.iop.org/article/10.1088/2634-4386/ac9b86/pdf","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":[{"score":0.8799999952316284,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":99,"referenced_works":["https://openalex.org/W1570411240","https://openalex.org/W1604973310","https://openalex.org/W1645800954","https://openalex.org/W1686810756","https://openalex.org/W1745334888","https://openalex.org/W1836465849","https://openalex.org/W1901129140","https://openalex.org/W1990540882","https://openalex.org/W1999085092","https://openalex.org/W2016574277","https://openalex.org/W2020676607","https://openalex.org/W2031489346","https://openalex.org/W2049511526","https://openalex.org/W2076661751","https://openalex.org/W2144187604","https://openalex.org/W2144794286","https://openalex.org/W2147101007","https://openalex.org/W2158083362","https://openalex.org/W2159951683","https://openalex.org/W2194775991","https://openalex.org/W2395611524","https://openalex.org/W2412782625","https://openalex.org/W2464708700","https://openalex.org/W2513853720","https://openalex.org/W2563705555","https://openalex.org/W2604319603","https://openalex.org/W2621826044","https://openalex.org/W2775079417","https://openalex.org/W2783525259","https://openalex.org/W2806066966","https://openalex.org/W2897802248","https://openalex.org/W2907965334","https://openalex.org/W2921676720","https://openalex.org/W2950514207","https://openalex.org/W2953303875","https://openalex.org/W2963335874","https://openalex.org/W2963727650","https://openalex.org/W2964309882","https://openalex.org/W2964338223","https://openalex.org/W2964402976","https://openalex.org/W2965867763","https://openalex.org/W2968428872","https://openalex.org/W2974328520","https://openalex.org/W2980526675","https://openalex.org/W2984844508","https://openalex.org/W2990793844","https://openalex.org/W2998119008","https://openalex.org/W3015205410","https://openalex.org/W3016500864","https://openalex.org/W3028752951","https://openalex.org/W3035644810","https://openalex.org/W3036016986","https://openalex.org/W3038819247","https://openalex.org/W3040318838","https://openalex.org/W3042725081","https://openalex.org/W3047826181","https://openalex.org/W3087030021","https://openalex.org/W3092055689","https://openalex.org/W3097285691","https://openalex.org/W3132455321","https://openalex.org/W3139657805","https://openalex.org/W3148322579","https://openalex.org/W3170967170","https://openalex.org/W3201424517","https://openalex.org/W3203196551","https://openalex.org/W3213984553","https://openalex.org/W4280536985","https://openalex.org/W4300167295","https://openalex.org/W6631782140","https://openalex.org/W6636972337","https://openalex.org/W6637373629","https://openalex.org/W6637573526","https://openalex.org/W6638667902","https://openalex.org/W6639824700","https://openalex.org/W6640054144","https://openalex.org/W6649797076","https://openalex.org/W6681666973","https://openalex.org/W6682925094","https://openalex.org/W6687483927","https://openalex.org/W6730845260","https://openalex.org/W6745178058","https://openalex.org/W6748481559","https://openalex.org/W6748869271","https://openalex.org/W6757855356","https://openalex.org/W6761121205","https://openalex.org/W6763957789","https://openalex.org/W6767047254","https://openalex.org/W6769315540","https://openalex.org/W6770181119","https://openalex.org/W6772750526","https://openalex.org/W6774340010","https://openalex.org/W6776001672","https://openalex.org/W6780750607","https://openalex.org/W6782262041","https://openalex.org/W6784993802","https://openalex.org/W6792899259","https://openalex.org/W6792915618","https://openalex.org/W6798444403","https://openalex.org/W6838465605"],"related_works":["https://openalex.org/W4281699635","https://openalex.org/W4321472116","https://openalex.org/W3036048022","https://openalex.org/W3202619090","https://openalex.org/W4309224979","https://openalex.org/W3102040318","https://openalex.org/W4287724471","https://openalex.org/W2786930404","https://openalex.org/W3214713078","https://openalex.org/W2944910788"],"abstract_inverted_index":{"Abstract":[0],"Spiking":[1],"neural":[2,14],"networks":[3,15,83,137],"(SNNs)":[4],"have":[5,32,63],"recently":[6],"emerged":[7],"as":[8,44],"the":[9,74,128,167,198],"low-power":[10],"alternative":[11],"to":[12,27,51,66,127,196,216],"artificial":[13],"(ANNs)":[16],"because":[17],"of":[18,36,131,200],"their":[19,28,52,217],"sparse,":[20],"asynchronous,":[21],"and":[22,47,54,79,103,123,146,164,185,191,213],"binary":[23],"event-driven":[24],"processing.":[25],"Due":[26],"energy":[29],"efficiency,":[30],"SNNs":[31,118,201,208],"a":[33],"high":[34,121],"possibility":[35],"being":[37],"deployed":[38],"for":[39,97,166,202],"real-world,":[40],"resource-constrained":[41],"systems":[42],"such":[43],"autonomous":[45],"vehicles":[46],"drones.":[48],"However,":[49],"owing":[50],"non-differentiable":[53],"complex":[55],"neuronal":[56],"dynamics,":[57],"most":[58],"previous":[59],"SNN":[60,75,94,168],"optimization":[61,95],"methods":[62],"been":[64],"limited":[65],"image":[67],"recognition.":[68],"In":[69,194],"this":[70,221],"paper,":[71],"we":[72,89,134,153,205],"explore":[73],"applications":[76],"beyond":[77],"classification":[78],"present":[80],"semantic":[81,108,175,203],"segmentation":[82,109,158,176,187],"configured":[84],"with":[85,138],"spiking":[86],"neurons.":[87],"Specifically,":[88],"first":[90],"investigate":[91],"two":[92,155],"representative":[93],"techniques":[96],"recognition":[98],"tasks":[99],"(i.e.,":[100,160],"ANN-SNN":[101,150],"conversion":[102],"surrogate":[104,139],"gradient":[105,140],"learning)":[106],"on":[107,173],"datasets.":[110,193],"We":[111,170],"observe":[112],"that,":[113],"when":[114],"converted":[115],"from":[116,120],"ANNs,":[117],"suffer":[119],"latency":[122,145],"low":[124],"performance":[125,148],"due":[126],"spatial":[129],"variance":[130],"features.":[132],"Therefore,":[133],"directly":[135],"train":[136],"learning,":[141],"resulting":[142],"in":[143,220],"lower":[144],"higher":[147],"than":[149],"conversion.":[151],"Moreover,":[152],"redesign":[154],"fundamental":[156],"ANN":[157,218],"architectures":[159],"Fully":[161],"Convolutional":[162],"Networks":[163],"DeepLab)":[165],"domain.":[169,222],"conduct":[171],"experiments":[172],"three":[174],"benchmarks":[177],"including":[178],"PASCAL":[179],"VOC2012":[180],"dataset,":[181,184],"DDD17":[182],"event-based":[183],"synthetic":[186],"dataset":[188],"combined":[189],"CIFAR10":[190],"MNIST":[192],"addition":[195],"showing":[197],"feasibility":[199],"segmentation,":[204],"show":[206],"that":[207],"can":[209],"be":[210],"more":[211],"robust":[212],"energy-efficient":[214],"compared":[215],"counterparts":[219]},"counts_by_year":[{"year":2026,"cited_by_count":11},{"year":2025,"cited_by_count":23},{"year":2024,"cited_by_count":20},{"year":2023,"cited_by_count":21},{"year":2022,"cited_by_count":4}],"updated_date":"2026-07-30T17:31:21.811387","created_date":"2025-10-10T00:00:00"}
