{"id":"https://openalex.org/W2735633774","doi":"https://doi.org/10.1109/ijcnn.2017.7966099","title":"Multi-layer unsupervised learning in a spiking convolutional neural network","display_name":"Multi-layer unsupervised learning in a spiking convolutional neural network","publication_year":2017,"publication_date":"2017-05-01","ids":{"openalex":"https://openalex.org/W2735633774","doi":"https://doi.org/10.1109/ijcnn.2017.7966099","mag":"2735633774"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2017.7966099","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2017.7966099","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Joint Conference on Neural Networks (IJCNN)","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/A5065400728","display_name":"Amirhossein Tavanaei","orcid":"https://orcid.org/0000-0002-6482-440X"},"institutions":[{"id":"https://openalex.org/I79516672","display_name":"University of Louisiana at Lafayette","ror":"https://ror.org/01x8rc503","country_code":"US","type":"education","lineage":["https://openalex.org/I2799628689","https://openalex.org/I79516672"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amirhossein Tavanaei","raw_affiliation_strings":["The Center for Advanced Computer Studies, University of Louisiana, Lafayette, LA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Center for Advanced Computer Studies, University of Louisiana, Lafayette, LA, USA","institution_ids":["https://openalex.org/I79516672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075357799","display_name":"Anthony S. Maida","orcid":"https://orcid.org/0000-0003-2586-2865"},"institutions":[{"id":"https://openalex.org/I79516672","display_name":"University of Louisiana at Lafayette","ror":"https://ror.org/01x8rc503","country_code":"US","type":"education","lineage":["https://openalex.org/I2799628689","https://openalex.org/I79516672"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anthony S. Maida","raw_affiliation_strings":["The Center for Advanced Computer Studies, University of Louisiana, Lafayette, LA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Center for Advanced Computer Studies, University of Louisiana, Lafayette, LA, USA","institution_ids":["https://openalex.org/I79516672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I79516672"],"apc_list":null,"apc_paid":null,"fwci":10.9968,"has_fulltext":false,"cited_by_count":71,"citation_normalized_percentile":{"value":0.99312868,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2023","last_page":"2030"},"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":0.9993000030517578,"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/T11601","display_name":"Neuroscience and Neural Engineering","score":0.9940999746322632,"subfield":{"id":"https://openalex.org/subfields/2804","display_name":"Cellular and Molecular 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/mnist-database","display_name":"MNIST database","score":0.7908716797828674},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7908276319503784},{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.760475754737854},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6690160632133484},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6479901075363159},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.610564112663269},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5757205486297607},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.544418215751648},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5241641998291016},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.4929978549480438},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.46393802762031555},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43407025933265686},{"id":"https://openalex.org/keywords/convolutional-code","display_name":"Convolutional code","score":0.4143398702144623},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.3112418055534363},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.26377567648887634},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.09894594550132751}],"concepts":[{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.7908716797828674},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7908276319503784},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.760475754737854},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6690160632133484},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6479901075363159},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.610564112663269},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5757205486297607},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.544418215751648},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5241641998291016},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.4929978549480438},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.46393802762031555},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43407025933265686},{"id":"https://openalex.org/C157899210","wikidata":"https://www.wikidata.org/wiki/Q1395022","display_name":"Convolutional code","level":3,"score":0.4143398702144623},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.3112418055534363},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.26377567648887634},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.09894594550132751},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2017.7966099","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2017.7966099","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.5899999737739563,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W104211377","https://openalex.org/W1501499051","https://openalex.org/W1645800954","https://openalex.org/W1895684722","https://openalex.org/W1985735234","https://openalex.org/W2002700944","https://openalex.org/W2007815184","https://openalex.org/W2008008156","https://openalex.org/W2020676607","https://openalex.org/W2025539936","https://openalex.org/W2051137788","https://openalex.org/W2056737172","https://openalex.org/W2065158671","https://openalex.org/W2068566049","https://openalex.org/W2106884367","https://openalex.org/W2110654393","https://openalex.org/W2112739286","https://openalex.org/W2112796928","https://openalex.org/W2131724064","https://openalex.org/W2131831448","https://openalex.org/W2133128597","https://openalex.org/W2137234026","https://openalex.org/W2137383364","https://openalex.org/W2145889472","https://openalex.org/W2158766867","https://openalex.org/W2163605009","https://openalex.org/W2190490644","https://openalex.org/W2260550436","https://openalex.org/W2419165387","https://openalex.org/W2474360776","https://openalex.org/W2513853720","https://openalex.org/W2551992665","https://openalex.org/W2951742412","https://openalex.org/W3103193585","https://openalex.org/W3106257432","https://openalex.org/W4231109964","https://openalex.org/W6679593666","https://openalex.org/W6679964793","https://openalex.org/W6680351714","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W4281699635","https://openalex.org/W4321472116","https://openalex.org/W3202619090","https://openalex.org/W3102040318","https://openalex.org/W4287724471","https://openalex.org/W3214713078","https://openalex.org/W2786930404","https://openalex.org/W3035000326","https://openalex.org/W2944910788","https://openalex.org/W3041589219"],"abstract_inverted_index":{"Spiking":[0],"neural":[1,44],"networks":[2,9,27],"(SNNs)":[3],"have":[4,31],"advantages":[5],"over":[6],"traditional,":[7],"non-spiking":[8],"with":[10,28],"respect":[11],"to":[12,34,141,191,204],"biorealism,":[13],"potential":[14],"for":[15,76,150,160,181],"low-power":[16],"hardware":[17],"implementations,":[18],"and":[19,127,164,174],"theoretical":[20],"computing":[21],"power.":[22],"However,":[23],"in":[24,50,169,187],"practice,":[25],"spiking":[26,42,56,85],"multi-layer":[29,144],"learning":[30,101,145],"proven":[32],"difficult":[33],"train.":[35],"This":[36,103,156,193],"paper":[37],"explores":[38],"a":[39,51,60,65,83,96,143,170],"novel,":[40],"bio-inspired":[41,73],"convolutional":[43,78,135,173],"network":[45,201],"(CNN)":[46],"that":[47,133,199],"is":[48,118,137,153,158,186,202],"trained":[49,81],"greedy,":[52],"layer-wise":[53],"fashion.":[54],"The":[55,91,115,147,178],"CNN":[57],"consists":[58],"of":[59,70,172,195],"convolutional/pooling":[61],"layer":[62,79,94,104,136],"followed":[63],"by":[64,161],"feature":[66,92,175],"discovery":[67,93,176],"layer,":[68],"both":[69],"which":[71],"undergo":[72],"learning.":[74],"Kernels":[75],"the":[77,121,134,162,183,188,200],"are":[80],"using":[82,109,125],"sparse,":[84],"auto-encoder":[86],"representing":[87],"primary":[88],"visual":[89,107,166],"features.":[90],"uses":[95],"probabilistic":[97],"spike-timing-dependent":[98],"plasticity":[99],"(STDP)":[100],"rule.":[102],"represents":[105],"complex":[106],"features":[108,167],"WTA-thresholded,":[110],"leaky,":[111],"integrate-and-fire":[112],"(LIF)":[113],"neurons.":[114],"new":[116],"model":[117],"evaluated":[119],"on":[120],"MNIST":[122],"digit":[123],"dataset":[124],"clean":[126,151],"noisy":[128,184],"images.":[129],"Intermediate":[130],"results":[131],"show":[132],"stack-admissible,":[138],"enabling":[139],"it":[140],"support":[142],"architecture.":[146],"recognition":[148],"performance":[149,157,179,196],"images":[152,185],"above":[154],"98%.":[155],"accounted":[159],"independent":[163],"informative":[165],"extracted":[168],"hierarchy":[171],"layers.":[177],"loss":[180,197],"recognizing":[182],"range":[189],"0.1%":[190],"8.5%.":[192],"level":[194],"indicates":[198],"robust":[203],"additive":[205],"noise.":[206]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":15},{"year":2020,"cited_by_count":11},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":9}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
