{"id":"https://openalex.org/W4372260058","doi":"https://doi.org/10.1109/icassp49357.2023.10095560","title":"Efficient Similarity-Based Passive Filter Pruning for Compressing CNNS","display_name":"Efficient Similarity-Based Passive Filter Pruning for Compressing CNNS","publication_year":2023,"publication_date":"2023-05-05","ids":{"openalex":"https://openalex.org/W4372260058","doi":"https://doi.org/10.1109/icassp49357.2023.10095560"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49357.2023.10095560","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49357.2023.10095560","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-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/A5059302295","display_name":"Arshdeep Singh","orcid":"https://orcid.org/0000-0003-3465-0952"},"institutions":[{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Arshdeep Singh","raw_affiliation_strings":["University of Surrey,Centre for Vision, Speech and Signal Processing (CVSSP),UK","Centre for Vision, Speech and Signal Processing (CVSSP), University of Surrey, UK"],"affiliations":[{"raw_affiliation_string":"University of Surrey,Centre for Vision, Speech and Signal Processing (CVSSP),UK","institution_ids":["https://openalex.org/I28290843"]},{"raw_affiliation_string":"Centre for Vision, Speech and Signal Processing (CVSSP), University of Surrey, UK","institution_ids":["https://openalex.org/I28290843"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066967599","display_name":"Mark D. Plumbley","orcid":"https://orcid.org/0000-0002-9708-1075"},"institutions":[{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Mark D. Plumbley","raw_affiliation_strings":["University of Surrey,Centre for Vision, Speech and Signal Processing (CVSSP),UK","Centre for Vision, Speech and Signal Processing (CVSSP), University of Surrey, UK"],"affiliations":[{"raw_affiliation_string":"University of Surrey,Centre for Vision, Speech and Signal Processing (CVSSP),UK","institution_ids":["https://openalex.org/I28290843"]},{"raw_affiliation_string":"Centre for Vision, Speech and Signal Processing (CVSSP), University of Surrey, UK","institution_ids":["https://openalex.org/I28290843"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5059302295"],"corresponding_institution_ids":["https://openalex.org/I28290843"],"apc_list":null,"apc_paid":null,"fwci":0.61,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.63240909,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11309","display_name":"Music and Audio Processing","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10860","display_name":"Speech and Audio Processing","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10822","display_name":"Acoustic Wave Phenomena Research","score":0.9889000058174133,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.7187825441360474},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6580607295036316},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.6477951407432556},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6403277516365051},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.6221824884414673},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5302642583847046},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5230287313461304},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5229771137237549},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5068703293800354},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.48967888951301575},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4395730197429657},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4139768183231354},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2965748608112335},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.12630850076675415},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.10191813111305237}],"concepts":[{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.7187825441360474},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6580607295036316},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.6477951407432556},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6403277516365051},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.6221824884414673},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5302642583847046},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5230287313461304},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5229771137237549},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5068703293800354},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.48967888951301575},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4395730197429657},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4139768183231354},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2965748608112335},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.12630850076675415},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.10191813111305237},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","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},{"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:10.1109/icassp49357.2023.10095560","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49357.2023.10095560","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8857457899","display_name":null,"funder_award_id":"EP/T019751/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W2123469553","https://openalex.org/W2495425901","https://openalex.org/W2526050071","https://openalex.org/W2701719801","https://openalex.org/W2883111419","https://openalex.org/W2928560789","https://openalex.org/W2937439989","https://openalex.org/W2952899695","https://openalex.org/W2962949934","https://openalex.org/W2962965870","https://openalex.org/W2963759574","https://openalex.org/W3005225358","https://openalex.org/W3034513523","https://openalex.org/W3043781581","https://openalex.org/W3139123974","https://openalex.org/W3165945839","https://openalex.org/W4295723153","https://openalex.org/W4296070204","https://openalex.org/W4311415687","https://openalex.org/W6681017033","https://openalex.org/W6683826617","https://openalex.org/W6723181079","https://openalex.org/W6726275242","https://openalex.org/W6739717535","https://openalex.org/W6752516136","https://openalex.org/W6772849459","https://openalex.org/W6780864004","https://openalex.org/W6792390701"],"related_works":["https://openalex.org/W2487162673","https://openalex.org/W2793211469","https://openalex.org/W2949152769","https://openalex.org/W4372354731","https://openalex.org/W2942366970","https://openalex.org/W2807634898","https://openalex.org/W1692008701","https://openalex.org/W2597588799","https://openalex.org/W4360593462","https://openalex.org/W2562400057"],"abstract_inverted_index":{"Convolution":[0],"neural":[1],"networks":[2],"(CNNs)":[3],"have":[4],"shown":[5],"great":[6],"success":[7],"in":[8,98,152],"various":[9],"applications.":[10],"However,":[11,73],"the":[12,33,37,59,74,79,95,100,112,149,160,174,185,193],"computational":[13,75,96],"complexity":[14,76,97],"and":[15,36,61,144,209],"memory":[16,38],"storage":[17],"of":[18,40,77,123,159,192],"CNNs":[19,41,155,200],"is":[20,83,117,140,197],"a":[21,54,63,69,87,121,128,166,210],"bottleneck":[22],"for":[23,58,154,214],"their":[24],"deployment":[25],"on":[26,199],"resource-constrained":[27],"devices.":[28],"Recent":[29],"efforts":[30],"towards":[31],"reducing":[32],"computation":[34],"cost":[35],"overhead":[39],"involve":[42],"similarity-based":[43,135,161,177],"passive":[44,49,136],"filter":[45,50,137],"pruning":[46,51,138,162,178,188,195],"methods.":[47,189],"Similarity-based":[48],"methods":[52],"compute":[53],"pairwise":[55,80,101,114,168],"similarity":[56,81,102,115,169],"matrix":[57,82,116],"filters":[60,66],"eliminate":[62],"few":[64,122],"similar":[65],"to":[67,106,157],"obtain":[68],"small":[70],"pruned":[71],"CNN.":[72],"computing":[78],"high,":[84],"particularly":[85],"when":[86],"convolutional":[88],"layer":[89],"has":[90],"many":[91],"filters.":[92],"To":[93],"reduce":[94],"obtaining":[99],"matrix,":[103],"we":[104],"propose":[105],"use":[107],"an":[108],"efficient":[109,134,176],"method":[110,139,163,179,196],"where":[111],"complete":[113,167],"approximated":[118],"from":[119,172],"only":[120],"its":[124],"columns":[125],"by":[126],"using":[127],"Nystr\u00f6m":[129],"approximation":[130],"method.":[131],"The":[132,190],"proposed":[133,175,194],"3":[141],"times":[142],"faster":[143],"gives":[145],"same":[146,150],"accuracy":[147],"at":[148],"reduction":[151],"computations":[153],"compared":[156],"that":[158,164],"computes":[165],"matrix.":[170],"Apart":[171],"this,":[173],"performs":[180],"similarly":[181],"or":[182],"better":[183],"than":[184],"existing":[186],"norm-based":[187],"efficacy":[191],"evaluated":[198],"such":[201],"as":[202],"DCASE":[203],"2021":[204],"Task":[205],"1A":[206],"baseline":[207],"network":[208,212],"VGGish":[211],"designed":[213],"acoustic":[215],"scene":[216],"classification.":[217]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"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"}