{"id":"https://openalex.org/W4416674895","doi":"https://doi.org/10.7717/peerj-cs.3388","title":"Towards optimal sparse CNNs: sparsity-friendly knowledge distillation through feature decoupling","display_name":"Towards optimal sparse CNNs: sparsity-friendly knowledge distillation through feature decoupling","publication_year":2025,"publication_date":"2025-11-25","ids":{"openalex":"https://openalex.org/W4416674895","doi":"https://doi.org/10.7717/peerj-cs.3388"},"language":"en","primary_location":{"id":"doi:10.7717/peerj-cs.3388","is_oa":true,"landing_page_url":"https://doi.org/10.7717/peerj-cs.3388","pdf_url":"https://peerj.com/articles/cs-3388.pdf","source":{"id":"https://openalex.org/S4210178049","display_name":"PeerJ Computer Science","issn_l":"2376-5992","issn":["2376-5992"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320104","host_organization_name":"PeerJ, Inc.","host_organization_lineage":["https://openalex.org/P4310320104"],"host_organization_lineage_names":["PeerJ, Inc."],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PeerJ Computer Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://peerj.com/articles/cs-3388.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101664667","display_name":"Weihong He","orcid":"https://orcid.org/0000-0003-4507-5447"},"institutions":[{"id":"https://openalex.org/I4210103346","display_name":"Nanfang Hospital","ror":"https://ror.org/01eq10738","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210103346"]},{"id":"https://openalex.org/I4400600959","display_name":"Nanfang College Guangzhou","ror":"https://ror.org/04vrxqg89","country_code":null,"type":"education","lineage":["https://openalex.org/I4400600959"]},{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weihong He","raw_affiliation_strings":["School of Electrical and Computer Engineering, Nanfang College Guangzhou, Guangzhou, China","School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Nanfang College Guangzhou, Guangzhou, China","institution_ids":["https://openalex.org/I4210103346","https://openalex.org/I4400600959"]},{"raw_affiliation_string":"School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073147310","display_name":"Yuli Fu","orcid":"https://orcid.org/0000-0002-6548-446X"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuli Fu","raw_affiliation_strings":["School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032501113","display_name":"Youjun Xiang","orcid":"https://orcid.org/0000-0002-2109-948X"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youjun Xiang","raw_affiliation_strings":["School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101664667"],"corresponding_institution_ids":["https://openalex.org/I4210103346","https://openalex.org/I4400600959","https://openalex.org/I90610280"],"apc_list":{"value":1395,"currency":"USD","value_usd":1395},"apc_paid":{"value":1395,"currency":"USD","value_usd":1395},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.33118388,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"11","issue":null,"first_page":"e3388","last_page":"e3388"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.6705999970436096,"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":0.6705999970436096,"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":0.14720000326633453,"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/T11448","display_name":"Face recognition and analysis","score":0.02280000038444996,"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/pooling","display_name":"Pooling","score":0.7985000014305115},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.698199987411499},{"id":"https://openalex.org/keywords/decoupling","display_name":"Decoupling (probability)","score":0.5631999969482422},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.5138000249862671},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4122999906539917},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4072999954223633}],"concepts":[{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.7985000014305115},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7271999716758728},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.698199987411499},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6040999889373779},{"id":"https://openalex.org/C205606062","wikidata":"https://www.wikidata.org/wiki/Q5249645","display_name":"Decoupling (probability)","level":2,"score":0.5631999969482422},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5609999895095825},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.5138000249862671},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4122999906539917},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4072999954223633},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3952000141143799},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.3440000116825104},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.31470000743865967},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2653999924659729},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.2535000145435333},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.2533999979496002},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.25209999084472656}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.7717/peerj-cs.3388","is_oa":true,"landing_page_url":"https://doi.org/10.7717/peerj-cs.3388","pdf_url":"https://peerj.com/articles/cs-3388.pdf","source":{"id":"https://openalex.org/S4210178049","display_name":"PeerJ Computer Science","issn_l":"2376-5992","issn":["2376-5992"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320104","host_organization_name":"PeerJ, Inc.","host_organization_lineage":["https://openalex.org/P4310320104"],"host_organization_lineage_names":["PeerJ, Inc."],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PeerJ Computer Science","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:97cebb586e174fce8436bdcaacc98e23","is_oa":true,"landing_page_url":"https://doaj.org/article/97cebb586e174fce8436bdcaacc98e23","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"PeerJ Computer Science, Vol 11, p e3388 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.7717/peerj-cs.3388","is_oa":true,"landing_page_url":"https://doi.org/10.7717/peerj-cs.3388","pdf_url":"https://peerj.com/articles/cs-3388.pdf","source":{"id":"https://openalex.org/S4210178049","display_name":"PeerJ Computer Science","issn_l":"2376-5992","issn":["2376-5992"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320104","host_organization_name":"PeerJ, Inc.","host_organization_lineage":["https://openalex.org/P4310320104"],"host_organization_lineage_names":["PeerJ, Inc."],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PeerJ Computer Science","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416674895.pdf","grobid_xml":"https://content.openalex.org/works/W4416674895.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W1821462560","https://openalex.org/W2739879705","https://openalex.org/W2764043458","https://openalex.org/W2787680366","https://openalex.org/W2808133870","https://openalex.org/W2829536470","https://openalex.org/W2915589364","https://openalex.org/W2963140444","https://openalex.org/W2964118293","https://openalex.org/W2972343638","https://openalex.org/W2996970889","https://openalex.org/W3162847008","https://openalex.org/W3212622989","https://openalex.org/W4205581758","https://openalex.org/W4226283624","https://openalex.org/W4226396876","https://openalex.org/W4287769184","https://openalex.org/W4296414566","https://openalex.org/W4297218068","https://openalex.org/W4312929415","https://openalex.org/W4375869381","https://openalex.org/W4377130896","https://openalex.org/W4378506785","https://openalex.org/W4386072392","https://openalex.org/W4389072615","https://openalex.org/W4390908058","https://openalex.org/W4391305696"],"related_works":[],"abstract_inverted_index":{"Despite":[0],"the":[1,8,15,42,62,81,111,129,151,154,183],"efficacy":[2],"of":[3,10,17,44,84,153,185],"network":[4],"sparsity":[5],"in":[6,58,73],"reducing":[7],"complexity":[9],"convolutional":[11],"neural":[12],"networks":[13,19,52],"(CNNs),":[14],"performance":[16,43,180],"sparse":[18,51,67,124],"often":[20],"deteriorates":[21],"significantly":[22],"compared":[23],"to":[24,40,118,158],"their":[25],"dense":[26,87],"counterparts.":[27],"Knowledge":[28],"distillation":[29,105,122],"is":[30],"regarded":[31],"as":[32],"a":[33,101],"potent":[34],"strategy":[35],"for":[36,50,123],"utilizing":[37],"large":[38],"models":[39,69,88],"augment":[41],"smaller":[45],"counterparts;":[46],"however,":[47],"its":[48],"advantages":[49],"remain":[53],"substantially":[54],"constrained.":[55],"We":[56],"identify":[57],"this":[59,97],"article":[60],"that":[61,89],"underlying":[63],"issue":[64],"stems":[65],"from":[66,86],"student":[68],"exhibiting":[70],"disparate":[71],"behaviors":[72],"processing":[74],"foreground":[75,130],"and":[76,131,138,173,175],"background":[77,132],"features,":[78],"thereby":[79],"hindering":[80],"uniform":[82],"transfer":[83],"knowledge":[85,104,121],"address":[90],"both":[91],"feature":[92,113,116,145],"types":[93,114],"concurrently.":[94],"Building":[95],"on":[96,163],"insight,":[98],"we":[99,127,148],"introduce":[100],"novel":[102],"sparsity-friendly":[103],"(SF-KD)":[106],"method,":[107],"which":[108],"independently":[109],"supervises":[110],"two":[112,155],"using":[115],"decoupling":[117],"facilitate":[119],"effective":[120],"networks.":[125],"Specifically,":[126],"decouple":[128],"features":[133],"through":[134],"unique":[135],"pooling":[136],"techniques":[137],"implement":[139],"separate":[140],"mean":[141],"squared":[142],"error":[143],"(MSE)":[144],"distillation.":[146],"Furthermore,":[147],"dynamically":[149],"adjust":[150],"weights":[152],"loss":[156],"components":[157],"optimize":[159],"performance.":[160],"Experimental":[161],"results":[162],"Canadian":[164],"Institute":[165],"For":[166],"Advanced":[167],"Research":[168],"(CIFAR)":[169],"datasets":[170],"(including":[171],"CIFAR-10":[172],"CIFAR-100)":[174],"Mini-ImageNet":[176],"benchmarks":[177],"substantiate":[178],"significant":[179],"enhancements,":[181],"underscoring":[182],"effectiveness":[184],"our":[186],"proposed":[187],"methodology.":[188]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-11-25T00:00:00"}