{"id":"https://openalex.org/W4323520840","doi":"https://doi.org/10.1109/ieeeconf56349.2022.10051999","title":"Performance and Runtime Improvement of Spiking Convolutional Neural Networks","display_name":"Performance and Runtime Improvement of Spiking Convolutional Neural Networks","publication_year":2022,"publication_date":"2022-10-31","ids":{"openalex":"https://openalex.org/W4323520840","doi":"https://doi.org/10.1109/ieeeconf56349.2022.10051999"},"language":"en","primary_location":{"id":"doi:10.1109/ieeeconf56349.2022.10051999","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ieeeconf56349.2022.10051999","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 56th Asilomar Conference on Signals, Systems, and Computers","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/A5016446689","display_name":"Shahriar Rezghi Shirsavar","orcid":"https://orcid.org/0000-0002-7041-1804"},"institutions":[{"id":"https://openalex.org/I23946033","display_name":"University of Tehran","ror":"https://ror.org/05vf56z40","country_code":"IR","type":"education","lineage":["https://openalex.org/I23946033"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Shahriar Rezghi Shirsavar","raw_affiliation_strings":["School of Electrical and Computer Engineering, College of Engineering, University of Tehran,Tehran,Iran","School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, College of Engineering, University of Tehran,Tehran,Iran","institution_ids":["https://openalex.org/I23946033"]},{"raw_affiliation_string":"School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran","institution_ids":["https://openalex.org/I23946033"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076796124","display_name":"Mohammad\u2010Reza A. Dehaqani","orcid":"https://orcid.org/0000-0003-4365-4365"},"institutions":[{"id":"https://openalex.org/I23946033","display_name":"University of Tehran","ror":"https://ror.org/05vf56z40","country_code":"IR","type":"education","lineage":["https://openalex.org/I23946033"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Mohammad-Reza A. Dehaqani","raw_affiliation_strings":["School of Electrical and Computer Engineering, College of Engineering, University of Tehran,Tehran,Iran","School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, College of Engineering, University of Tehran,Tehran,Iran","institution_ids":["https://openalex.org/I23946033"]},{"raw_affiliation_string":"School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran","institution_ids":["https://openalex.org/I23946033"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5016446689"],"corresponding_institution_ids":["https://openalex.org/I23946033"],"apc_list":null,"apc_paid":null,"fwci":0.0915,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.43180092,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"412","issue":null,"first_page":"801","last_page":"805"},"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":0.9997000098228455,"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/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9973999857902527,"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":0.8699026107788086},{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.8084210157394409},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7106765508651733},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6251594424247742},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.5835672616958618},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.572600245475769},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.47358161211013794},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.44791918992996216},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44699394702911377},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43282318115234375},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.43026214838027954},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4196310043334961},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.13231679797172546}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8699026107788086},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.8084210157394409},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7106765508651733},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6251594424247742},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.5835672616958618},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.572600245475769},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.47358161211013794},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.44791918992996216},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44699394702911377},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43282318115234375},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.43026214838027954},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4196310043334961},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.13231679797172546},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ieeeconf56349.2022.10051999","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ieeeconf56349.2022.10051999","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 56th Asilomar Conference on Signals, Systems, and Computers","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":0.8700000047683716}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1986246844","https://openalex.org/W2004915807","https://openalex.org/W2056631950","https://openalex.org/W2076964542","https://openalex.org/W2153564253","https://openalex.org/W2162003043","https://openalex.org/W2194775991","https://openalex.org/W2271476098","https://openalex.org/W2360921115","https://openalex.org/W2779025322","https://openalex.org/W2808419395","https://openalex.org/W2891137210","https://openalex.org/W2946092987","https://openalex.org/W3008199512","https://openalex.org/W3032483595","https://openalex.org/W4221151421","https://openalex.org/W6810006340"],"related_works":["https://openalex.org/W2140186469","https://openalex.org/W4390421286","https://openalex.org/W4280563792","https://openalex.org/W4389724018","https://openalex.org/W4318719684","https://openalex.org/W3183136280","https://openalex.org/W4318559728","https://openalex.org/W4206951940","https://openalex.org/W4382602594","https://openalex.org/W4387850423"],"abstract_inverted_index":{"Spiking":[0],"neural":[1,15,32],"networks":[2,26,33,38],"(SNNs)":[3],"have":[4,34],"closer":[5],"dynamics":[6],"to":[7,11,40,48,51,65,72,79,106,119,134],"the":[8,12,73,101,108,127],"brain":[9],"compared":[10],"current":[13],"deep":[14],"networks.":[16],"Their":[17],"low":[18],"power":[19],"consumption":[20],"and":[21,69,96,117,129],"sample":[22],"efficiency":[23],"make":[24],"these":[25],"interesting.":[27],"Recently,":[28],"several":[29],"spiking":[30],"convolutional":[31,135],"been":[35],"proposed.":[36],"These":[37],"aim":[39],"increase":[41],"biological":[42],"plausibility":[43],"while":[44],"creating":[45],"powerful":[46],"tools":[47],"be":[49],"applied":[50],"machine":[52],"learning":[53],"tasks.":[54],"Here,":[55],"we":[56],"suggest":[57],"a":[58],"network":[59,67,74],"structure":[60,124],"based":[61],"on":[62],"previous":[63],"work":[64],"improve":[66,120],"runtime":[68,128],"accuracy.":[70,121],"Improvements":[71],"include":[75],"reducing":[76],"training":[77],"iterations":[78],"only":[80,115],"once,":[81],"effectively":[82],"using":[83],"principal":[84],"component":[85],"analysis":[86],"(PCA)":[87],"dimension":[88],"reduction,":[89],"weight":[90],"quantization,":[91],"timed":[92],"outputs":[93],"for":[94],"classification,":[95],"better":[97],"hyperparameter":[98],"tuning.":[99],"Furthermore,":[100],"preprocessing":[102],"step":[103],"is":[104],"changed":[105],"allow":[107],"processing":[109],"of":[110,114],"colored":[111],"images":[112],"instead":[113],"black":[116],"white":[118],"The":[122],"proposed":[123],"significantly":[125],"reduces":[126],"introduces":[130],"an":[131],"efficient":[132],"approach":[133],"SNNs.":[136]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2025-12-24T23:09:58.560324","created_date":"2025-10-10T00:00:00"}