{"id":"https://openalex.org/W3022581078","doi":"https://doi.org/10.1587/transinf.2019edl8200","title":"Loss-Driven Channel Pruning of Convolutional Neural Networks","display_name":"Loss-Driven Channel Pruning of Convolutional Neural Networks","publication_year":2020,"publication_date":"2020-04-30","ids":{"openalex":"https://openalex.org/W3022581078","doi":"https://doi.org/10.1587/transinf.2019edl8200","mag":"3022581078"},"language":"en","primary_location":{"id":"doi:10.1587/transinf.2019edl8200","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transinf.2019edl8200","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E103.D/5/E103.D_2019EDL8200/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://www.jstage.jst.go.jp/article/transinf/E103.D/5/E103.D_2019EDL8200/_pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101532325","display_name":"Xin Long","orcid":"https://orcid.org/0000-0003-3338-3223"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin LONG","raw_affiliation_strings":["National University of Defense Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030783966","display_name":"Xiangrong Zeng","orcid":"https://orcid.org/0000-0002-4247-9684"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangrong ZENG","raw_affiliation_strings":["National University of Defense Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100418568","display_name":"Chen Chen","orcid":"https://orcid.org/0000-0003-3957-7061"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen CHEN","raw_affiliation_strings":["National University of Defense Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001902162","display_name":"Huaxin Xiao","orcid":"https://orcid.org/0000-0003-4524-2698"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huaxin XIAO","raw_affiliation_strings":["National University of Defense Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100770607","display_name":"Maojun Zhang","orcid":"https://orcid.org/0000-0001-6748-0545"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Maojun ZHANG","raw_affiliation_strings":["National University of Defense Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":null,"apc_paid":null,"fwci":0.1917,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.47149561,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"E103.D","issue":"5","first_page":"1190","last_page":"1194"},"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":0.9976999759674072,"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/T10320","display_name":"Neural Networks and Applications","score":0.9927999973297119,"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":0.854586124420166},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.8315805196762085},{"id":"https://openalex.org/keywords/flops","display_name":"FLOPS","score":0.8306771516799927},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7626126408576965},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.577837347984314},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.5651149749755859},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5425522923469543},{"id":"https://openalex.org/keywords/residual-neural-network","display_name":"Residual neural network","score":0.5168288350105286},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4891100525856018},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46941882371902466},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3546299338340759},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3435346484184265},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.1356777846813202},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.13493701815605164},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09864270687103271}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.854586124420166},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.8315805196762085},{"id":"https://openalex.org/C3826847","wikidata":"https://www.wikidata.org/wiki/Q188768","display_name":"FLOPS","level":2,"score":0.8306771516799927},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7626126408576965},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.577837347984314},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.5651149749755859},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5425522923469543},{"id":"https://openalex.org/C2944601119","wikidata":"https://www.wikidata.org/wiki/Q43744058","display_name":"Residual neural network","level":3,"score":0.5168288350105286},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4891100525856018},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46941882371902466},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3546299338340759},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3435346484184265},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.1356777846813202},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.13493701815605164},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09864270687103271},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1587/transinf.2019edl8200","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transinf.2019edl8200","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E103.D/5/E103.D_2019EDL8200/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1587/transinf.2019edl8200","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transinf.2019edl8200","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E103.D/5/E103.D_2019EDL8200/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.4300000071525574,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3022581078.pdf","grobid_xml":"https://content.openalex.org/works/W3022581078.grobid-xml"},"referenced_works_count":17,"referenced_works":["https://openalex.org/W1902934009","https://openalex.org/W2102605133","https://openalex.org/W2119144962","https://openalex.org/W2163605009","https://openalex.org/W2167215970","https://openalex.org/W2300242332","https://openalex.org/W2405920868","https://openalex.org/W2513419314","https://openalex.org/W2515385951","https://openalex.org/W2556833785","https://openalex.org/W2612445135","https://openalex.org/W2748428003","https://openalex.org/W2754084392","https://openalex.org/W2909577373","https://openalex.org/W2940141242","https://openalex.org/W2951886768","https://openalex.org/W2963125010"],"related_works":["https://openalex.org/W4315697128","https://openalex.org/W3005814217","https://openalex.org/W3134206242","https://openalex.org/W4287272376","https://openalex.org/W3092292339","https://openalex.org/W3213976941","https://openalex.org/W2604192360","https://openalex.org/W2958985755","https://openalex.org/W4360783045","https://openalex.org/W3160421061"],"abstract_inverted_index":{"The":[0],"increase":[1],"in":[2,19,95],"computation":[3],"cost":[4],"and":[5,62,65,84,105,107,121],"storage":[6],"of":[7,48],"convolutional":[8],"neural":[9],"networks":[10,32],"(CNNs)":[11],"severely":[12],"hinders":[13],"their":[14],"applications":[15],"on":[16],"limited-resources":[17],"devices":[18],"recent":[20],"years.":[21],"As":[22],"a":[23,41,78],"result,":[24],"there":[25],"is":[26,114],"impending":[27],"necessity":[28],"to":[29,44,60,116,133],"accelerate":[30],"the":[31,92,111],"by":[33,54,69],"certain":[34],"methods.":[35],"In":[36,87],"this":[37],"paper,":[38],"we":[39,76,90],"propose":[40],"loss-driven":[42],"method":[43,94,113],"prune":[45,117],"redundant":[46],"channels":[47,53,68,120],"CNNs.":[49],"It":[50],"identifies":[51],"unimportant":[52],"using":[55],"Taylor":[56],"expansion":[57],"technique":[58],"regarding":[59],"scaling":[61],"shifting":[63],"factors,":[64],"prunes":[66],"those":[67],"fixed":[70],"percentile":[71],"threshold.":[72],"By":[73],"doing":[74],"so,":[75],"obtain":[77,134],"compact":[79,136],"network":[80],"with":[81,98,123],"less":[82],"parameters":[83,122],"FLOPs":[85],"consumption.":[86],"experimental":[88,108],"section,":[89],"evaluate":[91],"proposed":[93,112],"CIFAR":[96],"datasets":[97],"several":[99],"popular":[100],"networks,":[101],"including":[102],"VGG-19,":[103],"DenseNet-40":[104],"ResNet-164,":[106],"results":[109],"demonstrate":[110],"able":[115],"over":[118],"70%":[119],"no":[124],"performance":[125],"loss.":[126],"Moreover,":[127],"iterative":[128],"pruning":[129],"could":[130],"be":[131],"used":[132],"more":[135],"network.":[137]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}