{"id":"https://openalex.org/W4379137329","doi":"https://doi.org/10.3233/ida-226810","title":"Filter pruning via feature map clustering","display_name":"Filter pruning via feature map clustering","publication_year":2023,"publication_date":"2023-06-02","ids":{"openalex":"https://openalex.org/W4379137329","doi":"https://doi.org/10.3233/ida-226810"},"language":"en","primary_location":{"id":"doi:10.3233/ida-226810","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ida-226810","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Data Analysis","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/A5100318457","display_name":"Wei Li","orcid":"https://orcid.org/0000-0003-4589-2711"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Li","raw_affiliation_strings":["College of Computer Science, Zhejiang University, Hangzhou, Zhejiang, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, Zhejiang University, Hangzhou, Zhejiang, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024723872","display_name":"Yongxing He","orcid":"https://orcid.org/0000-0003-3097-5477"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongxing He","raw_affiliation_strings":["College of Computer Science, Zhejiang University, Hangzhou, Zhejiang, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, Zhejiang University, Hangzhou, Zhejiang, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100419419","display_name":"Xiaoyu Zhang","orcid":"https://orcid.org/0000-0002-8057-3997"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyu Zhang","raw_affiliation_strings":["College of Computer Science, Zhejiang University, Hangzhou, Zhejiang, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, Zhejiang University, Hangzhou, Zhejiang, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010028964","display_name":"Yongchuan Tang","orcid":"https://orcid.org/0000-0001-9344-0491"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]},{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yongchuan Tang","raw_affiliation_strings":["Alibaba-Zhejiang University Joint Research Institute of Frontier Technologise, Hangzhou, Zhejiang, China","College of Computer Science, Zhejiang University, Hangzhou, Zhejiang, China"],"affiliations":[{"raw_affiliation_string":"Alibaba-Zhejiang University Joint Research Institute of Frontier Technologise, Hangzhou, Zhejiang, China","institution_ids":["https://openalex.org/I45928872","https://openalex.org/I76130692"]},{"raw_affiliation_string":"College of Computer Science, Zhejiang University, Hangzhou, Zhejiang, China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5010028964"],"corresponding_institution_ids":["https://openalex.org/I45928872","https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":0.369,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.58259878,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":"27","issue":"4","first_page":"911","last_page":"933"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9991999864578247,"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/redundancy","display_name":"Redundancy (engineering)","score":0.7425051927566528},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6828794479370117},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.5463278293609619},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5366840362548828},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5158364176750183},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46104592084884644},{"id":"https://openalex.org/keywords/flops","display_name":"FLOPS","score":0.45875903964042664},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.44593361020088196},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.42148882150650024},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.23691532015800476}],"concepts":[{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.7425051927566528},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6828794479370117},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.5463278293609619},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5366840362548828},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5158364176750183},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46104592084884644},{"id":"https://openalex.org/C3826847","wikidata":"https://www.wikidata.org/wiki/Q188768","display_name":"FLOPS","level":2,"score":0.45875903964042664},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44593361020088196},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.42148882150650024},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.23691532015800476},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/ida-226810","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ida-226810","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Data Analysis","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.5199999809265137}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1987971958","https://openalex.org/W2097117768","https://openalex.org/W2117539524","https://openalex.org/W2119112357","https://openalex.org/W2150593711","https://openalex.org/W2194775991","https://openalex.org/W2798170643","https://openalex.org/W2807961551","https://openalex.org/W2894994475","https://openalex.org/W2924515500","https://openalex.org/W2928560789","https://openalex.org/W2962851801","https://openalex.org/W2963145730","https://openalex.org/W2963363373","https://openalex.org/W2963382930","https://openalex.org/W2963446712","https://openalex.org/W2964233199","https://openalex.org/W2964266063","https://openalex.org/W2981383995","https://openalex.org/W2996896271","https://openalex.org/W3034342078","https://openalex.org/W3034513523","https://openalex.org/W3035156558","https://openalex.org/W3104263540","https://openalex.org/W3110378228","https://openalex.org/W3180849877","https://openalex.org/W3197252688","https://openalex.org/W3199015017","https://openalex.org/W6600075759","https://openalex.org/W6604381581"],"related_works":["https://openalex.org/W4382323155","https://openalex.org/W4315697128","https://openalex.org/W3205506801","https://openalex.org/W2971502891","https://openalex.org/W3183570023","https://openalex.org/W4287067436","https://openalex.org/W4280599700","https://openalex.org/W2986126107","https://openalex.org/W4323650687","https://openalex.org/W3092292339"],"abstract_inverted_index":{"With":[0],"the":[1,43,53,63,71,90,97,103,111,114,133,137,140,159,172,194],"help":[2],"of":[3,31,45,47,92,99,116,129,135,139,174,198],"network":[4,32,72],"compression":[5,33],"algorithms,":[6],"deep":[7],"neural":[8],"networks":[9],"can":[10],"be":[11,120],"applied":[12],"on":[13,148,177],"low-power":[14],"embedded":[15],"systems":[16],"and":[17,24,38,102,161,185,207],"mobile":[18],"devices":[19],"such":[20],"as":[21],"drones,":[22],"satellites,":[23],"smartphones.":[25],"Filter":[26],"pruning":[27,57,118,167],"is":[28,132,142],"a":[29,130,152],"sub-direction":[30],"research,":[34],"which":[35],"reduces":[36],"memory":[37],"computational":[39],"consumption":[40],"by":[41,95,122],"reducing":[42],"number":[44],"parameters":[46,205],"model":[48,179],"filters.":[49,58,105,146],"Previous":[50],"works":[51],"utilized":[52],"\u201cmore-simple-less-important\u201d":[54],"criterion":[55,153],"for":[56],"That":[59],"is,":[60],"filters":[61,160],"with":[62,89,110,144,190],"smaller":[64],"norm":[65],"or":[66],"more":[67],"sparse":[68],"weights":[69,94],"in":[70,196],"are":[73,84],"preferentially":[74],"pruned.":[75],"In":[76],"this":[77],"paper,":[78],"we":[79,107,150],"found":[80],"that":[81,113],"feature":[82,100],"maps":[83,101],"not":[85],"fully":[86],"positively":[87],"correlated":[88],"sparsity":[91],"filter":[93,117,131,141,166],"observing":[96],"visualization":[98],"corresponding":[104],"Hence,":[106],"came":[108],"up":[109],"idea":[112],"priority":[115],"should":[119],"determined":[121],"redundancy":[123,128,155],"rather":[124],"than":[125],"sparsity.":[126],"The":[127,187],"measure":[134],"whether":[136],"output":[138],"repeated":[143],"other":[145],"Based":[147],"this,":[149],"defined":[151],"called":[154],"index":[156],"to":[157],"rank":[158],"introduced":[162],"it":[163],"into":[164],"our":[165,175,191],"strategy.":[168],"Extensive":[169],"experiments":[170],"demonstrate":[171],"effectiveness":[173],"approach":[176],"different":[178],"architectures,":[180],"including":[181],"VGGNet,":[182],"GoogleNet,":[183],"DenseNet,":[184],"ResNet.":[186],"models":[188],"compressed":[189],"strategy":[192],"surpass":[193],"state-of-the-art":[195],"terms":[197],"Floating":[199],"Point":[200],"Operations":[201],"Per":[202],"Second":[203],"(FLOPs),":[204],"reduction,":[206],"classification":[208],"accuracy.":[209]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
