{"id":"https://openalex.org/W3046669193","doi":"https://doi.org/10.1109/tcsvt.2020.3013170","title":"SASL: Saliency-Adaptive Sparsity Learning for Neural Network Acceleration","display_name":"SASL: Saliency-Adaptive Sparsity Learning for Neural Network Acceleration","publication_year":2020,"publication_date":"2020-07-30","ids":{"openalex":"https://openalex.org/W3046669193","doi":"https://doi.org/10.1109/tcsvt.2020.3013170","mag":"3046669193"},"language":"en","primary_location":{"id":"doi:10.1109/tcsvt.2020.3013170","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2020.3013170","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Circuits and Systems for Video Technology","raw_type":"journal-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/A5100690272","display_name":"Jun Shi","orcid":"https://orcid.org/0000-0002-9888-6238"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Shi","raw_affiliation_strings":["CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System, University of Science and Technology of China, Hefei, China","CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System, University of Science and Technology of China, Hefei , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]},{"raw_affiliation_string":"CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System, University of Science and Technology of China, Hefei , China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101652522","display_name":"Jianfeng Xu","orcid":"https://orcid.org/0000-0003-1619-1967"},"institutions":[{"id":"https://openalex.org/I4210164495","display_name":"KDDI Research (Japan)","ror":"https://ror.org/05qsqt662","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210164495"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Jianfeng Xu","raw_affiliation_strings":["KDDI Research, Inc., Fujimino, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KDDI Research, Inc., Fujimino, Japan","institution_ids":["https://openalex.org/I4210164495"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079581959","display_name":"Kazuyuki Tasaka","orcid":null},"institutions":[{"id":"https://openalex.org/I4210164495","display_name":"KDDI Research (Japan)","ror":"https://ror.org/05qsqt662","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210164495"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kazuyuki Tasaka","raw_affiliation_strings":["KDDI Research, Inc., Fujimino, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KDDI Research, Inc., Fujimino, Japan","institution_ids":["https://openalex.org/I4210164495"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079572598","display_name":"Zhibo Chen","orcid":"https://orcid.org/0000-0002-8525-5066"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhibo Chen","raw_affiliation_strings":["CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System, University of Science and Technology of China, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0002-8525-5066","affiliations":[{"raw_affiliation_string":"CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.831,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.86172508,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"31","issue":"5","first_page":"2008","last_page":"2019"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9994000196456909,"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"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.7991651296615601},{"id":"https://openalex.org/keywords/flops","display_name":"FLOPS","score":0.7596889734268188},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.6809455156326294},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5830927491188049},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5661384463310242},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.5398421287536621},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5344592332839966},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5153850317001343},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.46356400847435},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.45973172783851624},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3236073851585388}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7991651296615601},{"id":"https://openalex.org/C3826847","wikidata":"https://www.wikidata.org/wiki/Q188768","display_name":"FLOPS","level":2,"score":0.7596889734268188},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.6809455156326294},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5830927491188049},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5661384463310242},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.5398421287536621},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5344592332839966},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5153850317001343},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.46356400847435},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.45973172783851624},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3236073851585388},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcsvt.2020.3013170","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2020.3013170","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Circuits and Systems for Video Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"},{"score":0.4399999976158142,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G1586809628","display_name":null,"funder_award_id":"2018AAA0101400","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G3634038634","display_name":null,"funder_award_id":"61632001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7172101008","display_name":null,"funder_award_id":"U1908209","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":95,"referenced_works":["https://openalex.org/W104184427","https://openalex.org/W639708223","https://openalex.org/W1677182931","https://openalex.org/W1686810756","https://openalex.org/W1799366690","https://openalex.org/W1903029394","https://openalex.org/W1923697677","https://openalex.org/W2097117768","https://openalex.org/W2114766824","https://openalex.org/W2117539524","https://openalex.org/W2119144962","https://openalex.org/W2125389748","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2331143823","https://openalex.org/W2495425901","https://openalex.org/W2520760693","https://openalex.org/W2582745083","https://openalex.org/W2613718673","https://openalex.org/W2758000438","https://openalex.org/W2788715907","https://openalex.org/W2798275680","https://openalex.org/W2805003733","https://openalex.org/W2807961551","https://openalex.org/W2808168148","https://openalex.org/W2886851211","https://openalex.org/W2891462450","https://openalex.org/W2893585013","https://openalex.org/W2899771611","https://openalex.org/W2909680570","https://openalex.org/W2924515500","https://openalex.org/W2928560789","https://openalex.org/W2928762566","https://openalex.org/W2945209373","https://openalex.org/W2947963429","https://openalex.org/W2948253213","https://openalex.org/W2950800384","https://openalex.org/W2951886768","https://openalex.org/W2952088488","https://openalex.org/W2962851801","https://openalex.org/W2962965870","https://openalex.org/W2963000224","https://openalex.org/W2963094099","https://openalex.org/W2963140066","https://openalex.org/W2963145730","https://openalex.org/W2963223345","https://openalex.org/W2963363373","https://openalex.org/W2963382930","https://openalex.org/W2963516811","https://openalex.org/W2963813662","https://openalex.org/W2963828549","https://openalex.org/W2964217527","https://openalex.org/W2964233199","https://openalex.org/W2964266063","https://openalex.org/W2964299589","https://openalex.org/W2965862774","https://openalex.org/W2970072941","https://openalex.org/W2970500560","https://openalex.org/W2971275988","https://openalex.org/W2976540144","https://openalex.org/W2978081181","https://openalex.org/W2984618279","https://openalex.org/W2990761096","https://openalex.org/W2996019573","https://openalex.org/W3034513523","https://openalex.org/W3118608800","https://openalex.org/W3137695714","https://openalex.org/W4295185264","https://openalex.org/W6604254268","https://openalex.org/W6620707391","https://openalex.org/W6637373629","https://openalex.org/W6638444622","https://openalex.org/W6640295612","https://openalex.org/W6677103964","https://openalex.org/W6677580257","https://openalex.org/W6678583879","https://openalex.org/W6684191040","https://openalex.org/W6714138976","https://openalex.org/W6723181079","https://openalex.org/W6725543821","https://openalex.org/W6726275242","https://openalex.org/W6729972426","https://openalex.org/W6732814185","https://openalex.org/W6745499552","https://openalex.org/W6748570084","https://openalex.org/W6751979845","https://openalex.org/W6755034786","https://openalex.org/W6755543212","https://openalex.org/W6756040250","https://openalex.org/W6762683066","https://openalex.org/W6763485134","https://openalex.org/W6763591946","https://openalex.org/W6767036268","https://openalex.org/W6767534822","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W4297676672","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W1585770001","https://openalex.org/W2075873371","https://openalex.org/W4245210885","https://openalex.org/W84383711","https://openalex.org/W4242351093"],"abstract_inverted_index":{"Accelerating":[0],"the":[1,17,33,44,93,99,106,113,122,139,150,157,177],"inference":[2],"of":[3,19,80,180,193],"CNNs":[4],"is":[5,85,88,109,146,166],"critical":[6],"to":[7,112,138,155],"their":[8],"deployment":[9],"in":[10,35,56,153],"real-world":[11],"applications.":[12],"Among":[13],"all":[14,49],"pruning":[15,151],"approaches,":[16],"methods":[18],"implementing":[20],"a":[21,66,161],"sparsity":[22,46,104],"learning":[23],"framework":[24],"have":[25],"shown":[26],"effectiveness":[27,171],"as":[28],"they":[29],"learn":[30],"and":[31,77,98,172,200],"prune":[32],"models":[34],"an":[36,57],"end-to-end":[37],"data-driven":[38],"manner.":[39],"However,":[40],"these":[41],"works":[42],"impose":[43],"same":[45],"regularization":[47,107],"on":[48,184],"filters":[50],"indiscriminately,":[51],"which":[52,87,142,168],"can":[53,119,189],"hardly":[54],"result":[55],"optimal":[58],"structure-sparse":[59],"network.":[60],"In":[61],"this":[62],"paper,":[63],"we":[64],"propose":[65],"Saliency-Adaptive":[67],"Sparsity":[68],"Learning":[69],"(SASL)":[70],"approach":[71,188],"for":[72,95,133],"further":[73],"optimization.":[74],"A":[75],"novel":[76],"effective":[78],"estimation":[79],"each":[81],"filter,":[82],"i.e.,":[83],"saliency,":[84,114],"designed,":[86],"measured":[89],"from":[90],"two":[91],"aspects:":[92],"importance":[94],"prediction":[96,123],"performance":[97,124,179],"consumed":[100],"computational":[101],"resources.":[102],"During":[103,149],"learning,":[105],"strength":[108],"adjusted":[110],"according":[111],"so":[115],"our":[116,144,181,187],"optimized":[117],"format":[118],"better":[120],"preserve":[121],"while":[125],"zeroing":[126],"out":[127],"more":[128],"computation-heavy":[129],"filters.":[130],"The":[131],"calculation":[132],"saliency":[134],"introduces":[135],"minimum":[136],"overhead":[137],"training":[140],"process,":[141],"means":[143],"SASL":[145],"very":[147,196],"efficient.":[148],"phase,":[152],"order":[154],"optimize":[156],"proposed":[158],"data-dependent":[159],"criterion,":[160],"hard":[162],"sample":[163],"mining":[164],"strategy":[165],"utilized,":[167],"shows":[169],"higher":[170],"efficiency.":[173],"Extensive":[174],"experiments":[175],"demonstrate":[176],"superior":[178],"method.":[182],"Notably,":[183],"ILSVRC-2012":[185],"dataset,":[186],"reduce":[190],"49.7%":[191],"FLOPs":[192],"ResNet-50":[194],"with":[195],"negligible":[197],"0.39%":[198],"top-1":[199],"0.05%":[201],"top-5":[202],"accuracy":[203],"degradation.":[204]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":3}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}
