{"id":"https://openalex.org/W2896611294","doi":"https://doi.org/10.1109/ijcnn.2018.8489339","title":"Fast and Efficient Deep Sparse Multi-Strength Spiking Neural Networks with Dynamic Pruning","display_name":"Fast and Efficient Deep Sparse Multi-Strength Spiking Neural Networks with Dynamic Pruning","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2896611294","doi":"https://doi.org/10.1109/ijcnn.2018.8489339","mag":"2896611294"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2018.8489339","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2018.8489339","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/A5029924052","display_name":"Ruizhi Chen","orcid":"https://orcid.org/0000-0001-6683-2342"},"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/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/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/A5100599300","display_name":"Pin Li","orcid":"https://orcid.org/0000-0003-1988-5390"},"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":4.2861,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.95652953,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"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/T10581","display_name":"Neural dynamics and brain function","score":0.9986000061035156,"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":0.996999979019165,"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/spiking-neural-network","display_name":"Spiking neural network","score":0.898878812789917},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8238958716392517},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.7028444409370422},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.6962457895278931},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6220914721488953},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5565452575683594},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.492710143327713},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4716821312904358},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.47156068682670593},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.386797159910202},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3787700831890106},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.22397255897521973}],"concepts":[{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.898878812789917},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8238958716392517},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.7028444409370422},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.6962457895278931},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6220914721488953},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5565452575683594},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.492710143327713},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4716821312904358},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.47156068682670593},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.386797159910202},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3787700831890106},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.22397255897521973},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2018.8489339","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2018.8489339","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":0.8899999856948853,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1645800954","https://openalex.org/W2002700944","https://openalex.org/W2008008156","https://openalex.org/W2020676607","https://openalex.org/W2074589580","https://openalex.org/W2107433900","https://openalex.org/W2112408199","https://openalex.org/W2112952404","https://openalex.org/W2116360511","https://openalex.org/W2119144962","https://openalex.org/W2138913040","https://openalex.org/W2145889472","https://openalex.org/W2162827630","https://openalex.org/W2165396124","https://openalex.org/W2165639766","https://openalex.org/W2170968634","https://openalex.org/W2276486856","https://openalex.org/W2285660444","https://openalex.org/W2300242332","https://openalex.org/W2314470091","https://openalex.org/W2319920447","https://openalex.org/W2405920868","https://openalex.org/W2513853720","https://openalex.org/W2521023735","https://openalex.org/W2549653513","https://openalex.org/W2562377059","https://openalex.org/W2569813014","https://openalex.org/W2594492285","https://openalex.org/W2625457103","https://openalex.org/W2657126969","https://openalex.org/W2742439472","https://openalex.org/W2775079417","https://openalex.org/W2963887857","https://openalex.org/W2964299589","https://openalex.org/W6651360156","https://openalex.org/W6669202587","https://openalex.org/W6677580257","https://openalex.org/W6698200048","https://openalex.org/W6700264148","https://openalex.org/W6714058667","https://openalex.org/W6727033975","https://openalex.org/W6730823560"],"related_works":["https://openalex.org/W2058965144","https://openalex.org/W2164382479","https://openalex.org/W2146343568","https://openalex.org/W98480971","https://openalex.org/W2150291671","https://openalex.org/W2013643406","https://openalex.org/W2027972911","https://openalex.org/W2157978810","https://openalex.org/W4391547476","https://openalex.org/W2097707447"],"abstract_inverted_index":{"Deep":[0],"convolutional":[1],"neural":[2],"networks":[3],"(CNNs)":[4],"have":[5],"shown":[6],"state-of-the-art":[7],"accuracy":[8,110,177],"for":[9,44,52,67,159],"various":[10],"computer":[11],"vision":[12],"and":[13,20,178],"speech":[14],"tasks.":[15],"However,":[16],"CNNs":[17,89],"are":[18,23,36,54,130],"computation-intensive":[19],"energy-inefficient":[21],"which":[22,40,145],"difficult":[24],"to":[25,58,82,200],"be":[26,71,171,198],"deployed":[27],"in":[28,73],"real-time":[29],"systems.":[30],"Event-driven":[31],"Spiking":[32],"Neural":[33],"Networks":[34],"(SNNs)":[35],"extremely":[37],"power":[38,46],"efficient,":[39],"provides":[41],"an":[42,138],"alternative":[43],"ultra-low":[45],"applications.":[47],"But":[48],"effective":[49],"training":[50,65],"methods":[51],"SNN":[53,106,120,128,142,169],"still":[55],"lacking.":[56],"Due":[57],"its":[59],"spatio-temporal":[60],"feature":[61,158],"of":[62,87,94,111,127,149],"SNN,":[63],"conventional":[64],"method":[66],"CNN":[68,174],"can":[69,170,197],"not":[70],"employed":[72],"SNN.":[74],"To":[75],"address":[76],"this":[77,134,165],"problem,":[78],"some":[79],"researchers":[80],"proposed":[81,137],"convert":[83],"the":[84,91,100,105,109,112,119,124,147,150,156,202,210],"corresponding":[85],"weights":[86,93],"trained":[88],"into":[90],"synapse":[92],"SNNs":[95,114],"(CNNs-SNNs).":[96],"Nevertheless,":[97],"limited":[98],"by":[99,205],"[0,":[101],"1]":[102],"constraints":[103],"on":[104],"neuron":[107,151],"outputs,":[108],"converted":[113,172],"is":[115,162],"impaired.":[116],"Besides,":[117],"as":[118],"network":[121],"becomes":[122],"deeper,":[123],"convergence":[125,188],"speed":[126],"inference":[129,180],"unacceptably":[131],"slow.":[132],"In":[133],"work,":[135],"we":[136],"innovative":[139],"deep":[140],"multi-strength":[141,192],"(M-SNN)":[143],"structure":[144],"relaxes":[146],"restriction":[148],"output":[152],"spike":[153],"strength":[154],"while":[155,208],"event-driven":[157],"low-power":[160],"implementations":[161],"maintained.":[163],"Using":[164],"architecture,":[166],"large":[167],"scale":[168],"from":[173],"with":[175,191],"comparable":[176],"fast":[179],"speed.":[181],"The":[182],"evaluation":[183],"results":[184],"show":[185],"3.7":[186],"\u00d7":[187],"speedup.":[189],"Moreover,":[190],"spike,":[193],"aggressive":[194],"pruning":[195],"strategies":[196],"applied":[199],"reduce":[201],"computational":[203],"operations":[204],"almost":[206],"85%":[207],"maintaining":[209],"same":[211],"accuracy.":[212]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}