{"id":"https://openalex.org/W4214929894","doi":"https://doi.org/10.1109/tcsvt.2022.3156588","title":"An Automatically Layer-Wise Searching Strategy for Channel Pruning Based on Task-Driven Sparsity Optimization","display_name":"An Automatically Layer-Wise Searching Strategy for Channel Pruning Based on Task-Driven Sparsity Optimization","publication_year":2022,"publication_date":"2022-03-03","ids":{"openalex":"https://openalex.org/W4214929894","doi":"https://doi.org/10.1109/tcsvt.2022.3156588"},"language":"en","primary_location":{"id":"doi:10.1109/tcsvt.2022.3156588","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2022.3156588","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/A5060765360","display_name":"Kaiyuan Feng","orcid":"https://orcid.org/0000-0003-4970-4175"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai-Yuan Feng","raw_affiliation_strings":["School of Electronic Engineering, Xidian University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0003-4970-4175","affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xia Fei","orcid":null},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xia Fei","raw_affiliation_strings":["School of Electronic Engineering, Xidian University, Xi’an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091227928","display_name":"Maoguo Gong","orcid":"https://orcid.org/0000-0002-0415-8556"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Maoguo Gong","raw_affiliation_strings":["School of Electronic Engineering, Xidian University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0002-0415-8556","affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006614329","display_name":"A. K. Qin","orcid":"https://orcid.org/0000-0001-6631-1651"},"institutions":[{"id":"https://openalex.org/I57093077","display_name":"Swinburne University of Technology","ror":"https://ror.org/031rekg67","country_code":"AU","type":"education","lineage":["https://openalex.org/I57093077"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"A. K. Qin","raw_affiliation_strings":["Department of Computing Technologies, Swinburne University of Technology, Hawthorn, VIC, Australia"],"raw_orcid":"https://orcid.org/0000-0001-6631-1651","affiliations":[{"raw_affiliation_string":"Department of Computing Technologies, Swinburne University of Technology, Hawthorn, VIC, Australia","institution_ids":["https://openalex.org/I57093077"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100348617","display_name":"Hao Li","orcid":"https://orcid.org/0000-0002-6294-6761"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Li","raw_affiliation_strings":["School of Electronic Engineering, Xidian University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0002-6294-6761","affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009576623","display_name":"Yue Wu","orcid":"https://orcid.org/0000-0002-3459-5079"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Wu","raw_affiliation_strings":["School of Computer Science and Technology, Xidian University, Xi’an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.2681,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":{"value":0.89368889,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"32","issue":"9","first_page":"5790","last_page":"5802"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9987999796867371,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9957000017166138,"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/pruning","display_name":"Pruning","score":0.8772430419921875},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7802040576934814},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6868046522140503},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.6398736238479614},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.617409884929657},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5598931312561035},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5365234613418579},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5096597671508789},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.49720123410224915},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4700019955635071},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.4580717086791992},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.45290523767471313},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.43455642461776733},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4221828579902649}],"concepts":[{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.8772430419921875},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7802040576934814},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6868046522140503},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.6398736238479614},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.617409884929657},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5598931312561035},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5365234613418579},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5096597671508789},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49720123410224915},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4700019955635071},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.4580717086791992},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.45290523767471313},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.43455642461776733},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4221828579902649},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","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},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcsvt.2022.3156588","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2022.3156588","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":[],"awards":[{"id":"https://openalex.org/G1949608614","display_name":null,"funder_award_id":"62036006","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2159723965","display_name":"Data-driven Traffic Analytics for Incident Analysis and Management","funder_award_id":"LP180100114","funder_id":"https://openalex.org/F4320334704","funder_display_name":"Australian Research Council"},{"id":"https://openalex.org/G3698760113","display_name":"Next-generation Intelligent Explorations of Geo-located Data ","funder_award_id":"DP200102611","funder_id":"https://openalex.org/F4320334704","funder_display_name":"Australian Research Council"},{"id":"https://openalex.org/G6545163668","display_name":null,"funder_award_id":"61906146","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/F4320334704","display_name":"Australian Research Council","ror":"https://ror.org/05mmh0f86"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W753847829","https://openalex.org/W1821462560","https://openalex.org/W1902041153","https://openalex.org/W1903029394","https://openalex.org/W1996901117","https://openalex.org/W2007339694","https://openalex.org/W2117539524","https://openalex.org/W2194775991","https://openalex.org/W2300242332","https://openalex.org/W2469490737","https://openalex.org/W2543539599","https://openalex.org/W2611669764","https://openalex.org/W2620998106","https://openalex.org/W2758000438","https://openalex.org/W2788715907","https://openalex.org/W2798534672","https://openalex.org/W2808168148","https://openalex.org/W2886851211","https://openalex.org/W2905544033","https://openalex.org/W2924515500","https://openalex.org/W2928560789","https://openalex.org/W2935381027","https://openalex.org/W2950656546","https://openalex.org/W2962851801","https://openalex.org/W2962861284","https://openalex.org/W2963145730","https://openalex.org/W2963223345","https://openalex.org/W2963363373","https://openalex.org/W2963382930","https://openalex.org/W2964051635","https://openalex.org/W2964233199","https://openalex.org/W2964266063","https://openalex.org/W2976540144","https://openalex.org/W2989808579","https://openalex.org/W2997006708","https://openalex.org/W2998310140","https://openalex.org/W3028304412","https://openalex.org/W3034408420","https://openalex.org/W3034513523","https://openalex.org/W3034528892","https://openalex.org/W3034797615","https://openalex.org/W3035467254","https://openalex.org/W3081111248","https://openalex.org/W3118608800","https://openalex.org/W3166490340","https://openalex.org/W4297775537","https://openalex.org/W6635477909","https://openalex.org/W6637373629","https://openalex.org/W6638667902","https://openalex.org/W6639703010","https://openalex.org/W6720242923","https://openalex.org/W6724998850","https://openalex.org/W6725543821","https://openalex.org/W6726275242","https://openalex.org/W6737664043","https://openalex.org/W6739917289","https://openalex.org/W6751979845","https://openalex.org/W6755034786","https://openalex.org/W6755843862","https://openalex.org/W6761601108","https://openalex.org/W6762450006","https://openalex.org/W6763726227","https://openalex.org/W6767064347","https://openalex.org/W6771654589","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W4386603768","https://openalex.org/W2950475743","https://openalex.org/W2886711096","https://openalex.org/W2750384547","https://openalex.org/W3036048022","https://openalex.org/W4309224979","https://openalex.org/W3088108839","https://openalex.org/W4300560302","https://openalex.org/W992687842","https://openalex.org/W3026879719"],"abstract_inverted_index":{"Deep":[0],"convolutional":[1],"neural":[2],"networks":[3],"(CNNs)":[4],"have":[5,129,221],"achieved":[6],"tremendous":[7],"successes":[8],"but":[9],"tend":[10],"to":[11,19,30,55,61,88,174,194,238],"suffer":[12,77],"from":[13,78],"high":[14],"computation":[15],"costs":[16],"mainly":[17],"due":[18],"heavy":[20],"over-parameterization,":[21],"resulting":[22],"in":[23,97,125,155,162,184,236,255],"the":[24,31,57,67,134,157,176,196,201,223,246,252],"difficulty":[25],"of":[26,66,122,248,257],"directly":[27],"applying":[28],"them":[29],"ever-growing":[32],"application":[33,90],"demands":[34],"based":[35,107,215],"on":[36,71,108,216,226],"low-end":[37],"edge":[38],"devices":[39],"with":[40],"strong":[41],"power":[42],"restriction":[43],"and":[44,111,114,116,234,260],"real-time":[45],"inference":[46],"requirement.":[47],"Recently,":[48],"there":[49],"has":[50],"much":[51],"research":[52],"attention":[53],"devoted":[54],"compressing":[56],"network":[58,127,208],"via":[59,112],"pruning":[60,74,136,153,178,218,241],"address":[62,145],"this":[63],"issue.":[64],"Most":[65],"existing":[68],"methods":[69],"rely":[70],"some":[72,227],"hand-designed":[73],"rules,":[75],"which":[76,92,132,156],"several":[79,239],"limitations.":[80],"Firstly,":[81],"manually":[82],"designed":[83,106],"rules":[84,103],"are":[85,104,160],"only":[86],"applicable":[87],"limited":[89],"scenarios,":[91],"can":[93],"hardly":[94],"generalize":[95],"well":[96],"a":[98,126,150,163,206],"broader":[99],"scope.":[100],"And":[101],"these":[102,146],"typically":[105],"human":[109],"experience":[110],"trial":[113],"error,":[115],"thus":[117],"highly":[118],"subjective.":[119],"Then,":[120],"channels":[121,159,214],"different":[123,182],"layers":[124,183],"may":[128],"diverse":[130],"distributions,":[131],"means":[133],"same":[135],"rule":[137,179],"is":[138,172,204],"not":[139],"appropriate":[140],"for":[141,181],"each":[142],"layer.":[143],"To":[144],"limitations,":[147],"we":[148,190],"propose":[149],"novel":[151],"channel":[152],"scheme,":[154],"task-irrelevant":[158],"removed":[161],"task-driven":[164],"manner.":[165],"Specifically,":[166],"an":[167],"adaptively":[168],"differentiable":[169],"search":[170],"module":[171],"proposed":[173,224],"find":[175],"best":[177],"automatically":[180],"CNNs":[185],"under":[186],"sparsity":[187],"constraints.":[188],"Besides,":[189],"employed":[191],"knowledge":[192],"distillation":[193],"alleviate":[195],"excessive":[197],"performance":[198],"loss.":[199],"Once":[200],"training":[202],"process":[203],"finished,":[205],"compact":[207],"will":[209],"be":[210],"obtained":[211],"by":[212],"removing":[213],"layer-wise":[217],"rules.":[219],"We":[220],"evaluated":[222],"method":[225,250],"well-known":[228],"benchmark":[229],"datasets":[230],"including":[231],"CIFAR,":[232],"MNIST,":[233],"ImageNet":[235],"comparison":[237],"state-of-the-art":[240],"methods.":[242],"Experimental":[243],"results":[244],"demonstrate":[245],"superiority":[247],"our":[249],"over":[251],"compared":[253],"ones":[254],"terms":[256],"both":[258],"parameters":[259],"FLOPs":[261],"reduction.":[262]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":3}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}