{"id":"https://openalex.org/W4383113538","doi":"https://doi.org/10.1109/ojcas.2023.3292109","title":"Slimmer CNNs Through Feature Approximation and Kernel Size Reduction","display_name":"Slimmer CNNs Through Feature Approximation and Kernel Size Reduction","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4383113538","doi":"https://doi.org/10.1109/ojcas.2023.3292109"},"language":"en","primary_location":{"id":"doi:10.1109/ojcas.2023.3292109","is_oa":true,"landing_page_url":"https://doi.org/10.1109/ojcas.2023.3292109","pdf_url":"https://ieeexplore.ieee.org/ielx7/8784029/8999500/10173478.pdf","source":{"id":"https://openalex.org/S4210192473","display_name":"IEEE Open Journal of Circuits and Systems","issn_l":"2644-1225","issn":["2644-1225"],"is_oa":true,"is_in_doaj":true,"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 Open Journal of Circuits and Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/8784029/8999500/10173478.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5051867610","display_name":"D. Nagaraju","orcid":"https://orcid.org/0000-0002-2221-5040"},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"education","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Dara Nagaraju","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, India"],"raw_orcid":"https://orcid.org/0000-0002-2221-5040","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, India","institution_ids":["https://openalex.org/I24676775"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009851991","display_name":"Nitin Chandrachoodan","orcid":"https://orcid.org/0000-0002-9258-7317"},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"education","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Nitin Chandrachoodan","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, India"],"raw_orcid":"https://orcid.org/0000-0002-9258-7317","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, India","institution_ids":["https://openalex.org/I24676775"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I24676775"],"apc_list":{"value":1750,"currency":"USD","value_usd":1750},"apc_paid":{"value":1750,"currency":"USD","value_usd":1750},"fwci":0.1064,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.36044524,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"4","issue":null,"first_page":"188","last_page":"202"},"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":0.9958999752998352,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9958999752998352,"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/kernel","display_name":"Kernel (algebra)","score":0.7544819116592407},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.7455103993415833},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7327659130096436},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6780446767807007},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6493523716926575},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6346216201782227},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.6055870056152344},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5077839493751526},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4645775258541107},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44449272751808167},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4321134686470032},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34902292490005493},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2623019218444824},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.22976922988891602},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.08314082026481628}],"concepts":[{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.7544819116592407},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.7455103993415833},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7327659130096436},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6780446767807007},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6493523716926575},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6346216201782227},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.6055870056152344},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5077839493751526},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4645775258541107},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44449272751808167},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4321134686470032},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34902292490005493},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2623019218444824},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.22976922988891602},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.08314082026481628},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ojcas.2023.3292109","is_oa":true,"landing_page_url":"https://doi.org/10.1109/ojcas.2023.3292109","pdf_url":"https://ieeexplore.ieee.org/ielx7/8784029/8999500/10173478.pdf","source":{"id":"https://openalex.org/S4210192473","display_name":"IEEE Open Journal of Circuits and Systems","issn_l":"2644-1225","issn":["2644-1225"],"is_oa":true,"is_in_doaj":true,"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 Open Journal of Circuits and Systems","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:c880e10e056d4eee9407eed60ce8f51e","is_oa":true,"landing_page_url":"https://doaj.org/article/c880e10e056d4eee9407eed60ce8f51e","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Open Journal of Circuits and Systems, Vol 4, Pp 188-202 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/ojcas.2023.3292109","is_oa":true,"landing_page_url":"https://doi.org/10.1109/ojcas.2023.3292109","pdf_url":"https://ieeexplore.ieee.org/ielx7/8784029/8999500/10173478.pdf","source":{"id":"https://openalex.org/S4210192473","display_name":"IEEE Open Journal of Circuits and Systems","issn_l":"2644-1225","issn":["2644-1225"],"is_oa":true,"is_in_doaj":true,"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 Open Journal of Circuits and Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.5099999904632568}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4383113538.pdf","grobid_xml":"https://content.openalex.org/works/W4383113538.grobid-xml"},"referenced_works_count":56,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1902934009","https://openalex.org/W1974078116","https://openalex.org/W1996901117","https://openalex.org/W1998917233","https://openalex.org/W2097117768","https://openalex.org/W2112796928","https://openalex.org/W2152839228","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2271840356","https://openalex.org/W2276892413","https://openalex.org/W2289252105","https://openalex.org/W2319920447","https://openalex.org/W2335728318","https://openalex.org/W2337344472","https://openalex.org/W2551176409","https://openalex.org/W2606722458","https://openalex.org/W2750173518","https://openalex.org/W2758000438","https://openalex.org/W2845210056","https://openalex.org/W2887870915","https://openalex.org/W2890248397","https://openalex.org/W2898997786","https://openalex.org/W2899206823","https://openalex.org/W2908735595","https://openalex.org/W2928762566","https://openalex.org/W2950248853","https://openalex.org/W2953106684","https://openalex.org/W2963048316","https://openalex.org/W2963223345","https://openalex.org/W2963526839","https://openalex.org/W2963881378","https://openalex.org/W2964905537","https://openalex.org/W3008725350","https://openalex.org/W3021291375","https://openalex.org/W3026337110","https://openalex.org/W3118608800","https://openalex.org/W3130554079","https://openalex.org/W6620707391","https://openalex.org/W6637373629","https://openalex.org/W6639703010","https://openalex.org/W6643777650","https://openalex.org/W6677103964","https://openalex.org/W6679667936","https://openalex.org/W6684191040","https://openalex.org/W6684563725","https://openalex.org/W6694517276","https://openalex.org/W6700264148","https://openalex.org/W6703116779","https://openalex.org/W6703414193","https://openalex.org/W6754218960","https://openalex.org/W6754219872","https://openalex.org/W6756165562","https://openalex.org/W6776676535","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W2949189996","https://openalex.org/W4312417841","https://openalex.org/W3200060857","https://openalex.org/W3006085271","https://openalex.org/W2319888919","https://openalex.org/W2767651786","https://openalex.org/W2912288872","https://openalex.org/W2295021132","https://openalex.org/W2963993660","https://openalex.org/W2796942851"],"abstract_inverted_index":{"Convolutional":[0,25],"Neural":[1],"Networks":[2],"(CNNs)":[3],"have":[4,51,182,197],"been":[5],"shown":[6],"to":[7,69,85,114,236],"achieve":[8,135,153],"state":[9],"of":[10,34,45,73,106,144,161,167,208,239],"the":[11,31,43,46,71,74,90,95,116,130,148,164,185,240,245],"art":[12],"results":[13],"on":[14,188,255],"several":[15,178],"image":[16],"processing":[17],"tasks":[18],"such":[19,252],"as":[20],"classification,":[21],"localization,":[22],"and":[23,26,98,243],"segmentation.":[24],"fully":[27],"connected":[28],"layers":[29,39,97],"form":[30],"building":[32],"blocks":[33],"these":[35],"networks.":[36],"The":[37],"convolution":[38,96],"are":[40],"responsible":[41],"for":[42,76,121,191,226],"majority":[44],"computations":[47,72,168,204],"even":[48],"though":[49],"they":[50],"fewer":[52],"parameters.":[53],"As":[54],"inference":[55],"is":[56,67],"used":[57],"much":[58],"more":[59],"than":[60],"training":[61],"(which":[62],"happens":[63],"only":[64,170,211],"once),":[65],"it":[66],"important":[68,92],"reduce":[70],"network":[75],"this":[77],"phase.":[78],"This":[79],"work":[80],"presents":[81],"a":[82,122,136,142,159,171,206,212,253],"systematic":[83],"procedure":[84],"trim":[86],"CNNs":[87],"by":[88],"identifying":[89],"least":[91],"features":[93],"in":[94,163,175,202,216,251],"replacing":[99],"them":[100],"either":[101],"with":[102,141,158,169,210,232],"approximations":[103],"or":[104],"kernels":[105],"reduced":[107],"size.":[108],"We":[109,126,181,218],"also":[110,183,219],"propose":[111],"an":[112,222],"algorithm":[113],"integrate":[115],"lower":[117,149],"kernel":[118,150,241],"approximation":[119,132],"technique":[120],"given":[123],"accuracy":[124,176],"budget.":[125],"show":[127,220],"that":[128,247],"using":[129],"linear":[131],"method":[133,151],"can":[134,152,229,248],"15":[137],"\u2013":[138,155],"80%":[139],"savings":[140,201],"median":[143,160,207],"52%":[145],"reduction":[146,157],"while":[147],"33":[154],"95%":[156],"65%":[162],"required":[165],"number":[166],"marginal":[172,213],"1%":[173],"loss":[174,215],"across":[177],"benchmark":[179],"datasets.":[180,193],"demonstrated":[184],"proposed":[186],"methods":[187],"VGG-16":[189,195],"architecture":[190],"various":[192],"On":[194],"we":[196],"achieved":[198],"4.2":[199],"-45%":[200],"MAC":[203],"(with":[205],"18.5%)":[209],"0.5%":[214],"accuracy.":[217],"how":[221],"existing":[223],"hardware":[224],"accelerator":[225],"DNNs":[227],"(DianNao)":[228],"be":[230,249],"modified":[231],"low":[233],"added":[234],"complexity":[235],"take":[237],"advantage":[238],"approximations,":[242],"estimate":[244],"speedups":[246],"obtained":[250],"way":[254],"custom":[256],"embedded":[257],"hardware.":[258]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
