{"id":"https://openalex.org/W2897623300","doi":"https://doi.org/10.1109/ijcnn.2018.8489400","title":"Low Latency Spiking ConvNets with Restricted Output Training and False Spike Inhibition","display_name":"Low Latency Spiking ConvNets with Restricted Output Training and False Spike Inhibition","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2897623300","doi":"https://doi.org/10.1109/ijcnn.2018.8489400","mag":"2897623300"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2018.8489400","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2018.8489400","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 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/A5101602321","display_name":"Ruizhi Chen","orcid":"https://orcid.org/0000-0001-7219-4658"},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruizhi Chen","raw_affiliation_strings":["dept. Institute of Automation, Chinese Academy of Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"dept. Institute of Automation, Chinese Academy of Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112127447","display_name":"Hong Ma","orcid":"https://orcid.org/0000-0002-4131-0297"},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Ma","raw_affiliation_strings":["dept. Institute of Automation, Chinese Academy of Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"dept. Institute of Automation, Chinese Academy of Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101595657","display_name":"Peng Guo","orcid":"https://orcid.org/0000-0002-8158-9982"},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Guo","raw_affiliation_strings":["dept. Institute of Automation, Chinese Academy of Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"dept. Institute of Automation, Chinese Academy of Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101610115","display_name":"Shaolin Xie","orcid":"https://orcid.org/0000-0001-5796-8862"},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaolin Xie","raw_affiliation_strings":["dept. Institute of Automation, Chinese Academy of Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"dept. Institute of Automation, Chinese Academy of Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100435494","display_name":"Ping Li","orcid":"https://orcid.org/0000-0002-1503-0240"},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pin Li","raw_affiliation_strings":["dept. Institute of Automation, Chinese Academy of Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"dept. Institute of Automation, Chinese Academy of Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100665183","display_name":"Donglin Wang","orcid":"https://orcid.org/0000-0003-1359-6440"},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Donglin Wang","raw_affiliation_strings":["dept. Institute of Automation, Chinese Academy of Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"dept. Institute of Automation, Chinese Academy of Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5586,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.81288678,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"95","issue":null,"first_page":"1","last_page":"8"},"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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9990000128746033,"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":0.9980999827384949,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.8323432803153992},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.8194800615310669},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8148092031478882},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6584029197692871},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.6212819814682007},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.60822594165802},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.5492656826972961},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5019886493682861},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49834537506103516},{"id":"https://openalex.org/keywords/spike","display_name":"Spike (software development)","score":0.4224083125591278},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3253292143344879},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.32376545667648315},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2087758183479309},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.20554402470588684}],"concepts":[{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.8323432803153992},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.8194800615310669},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8148092031478882},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6584029197692871},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.6212819814682007},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.60822594165802},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.5492656826972961},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5019886493682861},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49834537506103516},{"id":"https://openalex.org/C2781390188","wikidata":"https://www.wikidata.org/wiki/Q25203449","display_name":"Spike (software development)","level":2,"score":0.4224083125591278},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3253292143344879},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.32376545667648315},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2087758183479309},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.20554402470588684},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2018.8489400","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2018.8489400","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.9100000262260437,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W101771737","https://openalex.org/W1686810756","https://openalex.org/W2006370340","https://openalex.org/W2016708835","https://openalex.org/W2020096355","https://openalex.org/W2020676607","https://openalex.org/W2069552454","https://openalex.org/W2076063813","https://openalex.org/W2095705004","https://openalex.org/W2107433900","https://openalex.org/W2112796928","https://openalex.org/W2116360511","https://openalex.org/W2138913040","https://openalex.org/W2159951683","https://openalex.org/W2165639766","https://openalex.org/W2300242332","https://openalex.org/W2314470091","https://openalex.org/W2405920868","https://openalex.org/W2513148968","https://openalex.org/W2513853720","https://openalex.org/W2606722458","https://openalex.org/W2742439472","https://openalex.org/W2743130883","https://openalex.org/W2766422095","https://openalex.org/W2775079417","https://openalex.org/W2949117887","https://openalex.org/W2963114950","https://openalex.org/W2963157821","https://openalex.org/W2963887857","https://openalex.org/W2964299589"],"related_works":["https://openalex.org/W2058965144","https://openalex.org/W2542565870","https://openalex.org/W4306175885","https://openalex.org/W4312604567","https://openalex.org/W4387390134","https://openalex.org/W2165312143","https://openalex.org/W4251092571","https://openalex.org/W4297619707","https://openalex.org/W2583316550","https://openalex.org/W3110622310"],"abstract_inverted_index":{"Deep":[0],"convolutional":[1],"neural":[2,25],"networks":[3,26],"(ConvNets)":[4],"have":[5,61],"achieved":[6],"the":[7,42,63,76,79,85,96,100,113,118,128,137,140,153,166,176],"state-of-the-art":[8],"performance":[9],"on":[10,94,182],"many":[11],"real-world":[12],"applications.":[13],"However,":[14,75],"significant":[15],"computation":[16],"and":[17,32,127,174],"storage":[18],"demands":[19],"are":[20,125],"required":[21],"by":[22,84],"ConvNets.":[23],"Spiking":[24],"(SNNs),":[27],"with":[28,52,72],"sparsely":[29],"activated":[30],"neurons":[31],"event-driven":[33],"computations,":[34],"show":[35],"great":[36],"potential":[37],"to":[38,68,111,135,151],"take":[39],"advantage":[40],"of":[41,65,78,99,139,180],"ultra-":[43],"low":[44],"power":[45],"spike-based":[46],"hardware":[47],"architectures.":[48],"Yet,":[49],"training":[50,109,120],"SNN":[51],"similar":[53,73],"accuracy":[54,160,179],"as":[55],"ConvNets":[56,67,158],"is":[57,82,133],"difficult.":[58],"Recent":[59],"researchers":[60],"demonstrated":[62],"work":[64],"converting":[66],"SNNs":[69,81,168],"(CNN-SNN":[70],"conversion)":[71],"accuracy.":[74],"energy-efficiency":[77],"converted":[80,101,114,167],"impaired":[83],"increased":[86],"classification":[87,97,141,178],"latency.":[88],"In":[89],"this":[90],"paper,":[91],"we":[92,104,144],"focus":[93],"optimizing":[95],"latency":[98],"SNNs.":[102],"First,":[103],"propose":[105,145],"a":[106,146],"restricted":[107],"output":[108],"method":[110,150],"normalize":[112],"weights":[115],"dynamically":[116],"in":[117,157,170],"CNN-SNN":[119],"phase.":[121],"Second,":[122],"false":[123,129],"spikes":[124],"identified":[126],"spike":[130],"inhibition":[131],"theory":[132],"derived":[134],"speedup":[136],"convergence":[138],"process.":[142],"Third,":[143],"temporal":[147],"max":[148,154],"pooling":[149,155],"approximate":[152],"operation":[156],"without":[159],"loss.":[161],"The":[162],"evaluation":[163],"shows":[164],"that":[165],"converge":[169],"about":[171],"30":[172],"time-steps":[173],"achieve":[175],"best":[177],"94%":[181],"CIFAR":[183],"-10":[184],"dataset.":[185]},"counts_by_year":[{"year":2023,"cited_by_count":4},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
