{"id":"https://openalex.org/W4294891508","doi":"https://doi.org/10.1109/tnnls.2022.3201846","title":"Compression of Convolutional Neural Networks With Divergent Representation of Filters","display_name":"Compression of Convolutional Neural Networks With Divergent Representation of Filters","publication_year":2022,"publication_date":"2022-09-07","ids":{"openalex":"https://openalex.org/W4294891508","doi":"https://doi.org/10.1109/tnnls.2022.3201846","pmid":"https://pubmed.ncbi.nlm.nih.gov/36070270"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2022.3201846","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3201846","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5043565689","display_name":"Peng Lei","orcid":"https://orcid.org/0000-0001-7422-0258"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Lei","raw_affiliation_strings":["School of Electronic and Information Engineering, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7422-0258","affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004005455","display_name":"Jiawei Liang","orcid":"https://orcid.org/0000-0003-0748-3183"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiawei Liang","raw_affiliation_strings":["School of Electronic and Information Engineering, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-0748-3183","affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056894492","display_name":"Tong Zheng","orcid":"https://orcid.org/0000-0003-2251-6844"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tong Zheng","raw_affiliation_strings":["School of Electronic and Information Engineering, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100384655","display_name":"Jun Wang","orcid":"https://orcid.org/0000-0001-9223-2615"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Wang","raw_affiliation_strings":["School of Electronic and Information Engineering, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":0.4894,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.6243895,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"35","issue":"3","first_page":"4125","last_page":"4137"},"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/T10812","display_name":"Human Pose and Action Recognition","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"}},{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9986000061035156,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7908811569213867},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.769574761390686},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6658605337142944},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.555908739566803},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5534923076629639},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49036502838134766},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4210382103919983},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32811135053634644}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7908811569213867},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.769574761390686},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6658605337142944},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.555908739566803},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5534923076629639},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49036502838134766},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4210382103919983},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32811135053634644},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2022.3201846","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3201846","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:36070270","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36070270","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4099999964237213,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[{"id":"https://openalex.org/G8727693751","display_name":null,"funder_award_id":"2018ZC51022","funder_id":"https://openalex.org/F4320322857","funder_display_name":"Aeronautical Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320322857","display_name":"Aeronautical Science Foundation of China","ror":"https://ror.org/02wq41p38"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":66,"referenced_works":["https://openalex.org/W566555209","https://openalex.org/W1536680647","https://openalex.org/W1686810756","https://openalex.org/W1745334888","https://openalex.org/W1821462560","https://openalex.org/W1836465849","https://openalex.org/W1903029394","https://openalex.org/W1996901117","https://openalex.org/W2095705004","https://openalex.org/W2102605133","https://openalex.org/W2104636679","https://openalex.org/W2117539524","https://openalex.org/W2119144962","https://openalex.org/W2194775991","https://openalex.org/W2276892413","https://openalex.org/W2300242332","https://openalex.org/W2412782625","https://openalex.org/W2707890836","https://openalex.org/W2775811337","https://openalex.org/W2883111419","https://openalex.org/W2884751099","https://openalex.org/W2928560789","https://openalex.org/W2957577340","https://openalex.org/W2962851801","https://openalex.org/W2962965870","https://openalex.org/W2963223345","https://openalex.org/W2963363373","https://openalex.org/W2963393494","https://openalex.org/W2963446712","https://openalex.org/W2963674932","https://openalex.org/W2964233199","https://openalex.org/W2964266063","https://openalex.org/W2966256598","https://openalex.org/W2975381464","https://openalex.org/W2998543159","https://openalex.org/W3007122219","https://openalex.org/W3034513523","https://openalex.org/W3034674511","https://openalex.org/W3097642927","https://openalex.org/W3118608800","https://openalex.org/W3150698441","https://openalex.org/W3173390350","https://openalex.org/W3174700868","https://openalex.org/W3181161645","https://openalex.org/W3204647170","https://openalex.org/W4214700987","https://openalex.org/W4297775537","https://openalex.org/W4299823361","https://openalex.org/W6637373629","https://openalex.org/W6638060716","https://openalex.org/W6638444622","https://openalex.org/W6638632666","https://openalex.org/W6674330103","https://openalex.org/W6677103964","https://openalex.org/W6677580257","https://openalex.org/W6678583879","https://openalex.org/W6684191040","https://openalex.org/W6725543821","https://openalex.org/W6726275242","https://openalex.org/W6737664043","https://openalex.org/W6739917289","https://openalex.org/W6741783443","https://openalex.org/W6763207085","https://openalex.org/W6768080748","https://openalex.org/W6787972765","https://openalex.org/W6947681574"],"related_works":["https://openalex.org/W2357124094","https://openalex.org/W2387399993","https://openalex.org/W2389739210","https://openalex.org/W2348924972","https://openalex.org/W2365736347","https://openalex.org/W2047454415","https://openalex.org/W2070040999","https://openalex.org/W2387293848","https://openalex.org/W2250140200","https://openalex.org/W3121791438"],"abstract_inverted_index":{"Convolutional":[0],"neural":[1],"networks":[2],"(CNNs)":[3],"have":[4],"made":[5],"remarkable":[6],"achievements":[7],"in":[8,88,97,124,143],"many":[9],"tasks.":[10],"However,":[11],"most":[12],"of":[13,23,26,70],"them":[14],"are":[15,61,136],"hardly":[16],"applied":[17],"to":[18,43,52,139],"embedded":[19],"systems":[20],"directly":[21],"because":[22],"the":[24,68,120,125],"requirement":[25],"huge":[27],"memory":[28],"space":[29],"and":[30,45,65,122,146],"computing":[31],"power.":[32],"In":[33,107],"this":[34,73],"article,":[35],"we":[36],"propose":[37],"a":[38,75,109],"pruning":[39,77,83],"framework,":[40],"namely,":[41],"FiltDivNet,":[42],"accelerate":[44],"compress":[46],"CNN":[47,89,134,151],"models":[48,135],"for":[49,85,119],"their":[50,98],"applicability":[51],"small":[53],"or":[54],"portable":[55],"devices.":[56],"The":[57],"correlations":[58],"among":[59],"filters":[60,96],"taken":[62],"into":[63],"account":[64],"measured":[66],"by":[67,100,105],"goodness":[69],"fit.":[71],"On":[72],"basis,":[74],"hybrid-cluster":[76],"strategy":[78],"is":[79,117],"designed":[80],"with":[81,113,149],"dynamic":[82],"ratios":[84],"different":[86,150],"clusters":[87],"models.":[90],"It":[91],"aims":[92],"at":[93],"representing":[94],"its":[95,141,147],"diversity":[99],"removing":[101],"redundant":[102],"ones":[103],"cluster":[104],"cluster.":[106],"addition,":[108],"new":[110],"loss":[111],"function":[112],"adaptive":[114],"sparsity":[115],"constraints":[116],"introduced":[118],"retraining":[121],"fine-tuning":[123],"FiltDivNet.":[126],"Finally,":[127],"some":[128],"comparative":[129],"experiments":[130],"based":[131],"on":[132],"classical":[133],"carried":[137],"out":[138],"demonstrate":[140],"effectiveness":[142],"compression":[144],"performance":[145],"adaptability":[148],"architectures.":[152]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}