{"id":"https://openalex.org/W4385694585","doi":"https://doi.org/10.1109/ssp53291.2023.10207944","title":"A novel technique for optimizing the filter size of CNNs without backpropagation","display_name":"A novel technique for optimizing the filter size of CNNs without backpropagation","publication_year":2023,"publication_date":"2023-07-02","ids":{"openalex":"https://openalex.org/W4385694585","doi":"https://doi.org/10.1109/ssp53291.2023.10207944"},"language":"en","primary_location":{"id":"doi:10.1109/ssp53291.2023.10207944","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ssp53291.2023.10207944","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE Statistical Signal Processing Workshop (SSP)","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/A5104194966","display_name":"Muhammad Manzar Maqbool","orcid":null},"institutions":[{"id":"https://openalex.org/I184558857","display_name":"Royal Holloway University of London","ror":"https://ror.org/04g2vpn86","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I184558857"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Muhammad Manzar Maqbool","raw_affiliation_strings":["Royal Holloway University of London,Electronic Engineering Department,Egham,UK","Electronic Engineering Department, Royal Holloway University of London, Egham, UK"],"affiliations":[{"raw_affiliation_string":"Royal Holloway University of London,Electronic Engineering Department,Egham,UK","institution_ids":["https://openalex.org/I184558857"]},{"raw_affiliation_string":"Electronic Engineering Department, Royal Holloway University of London, Egham, UK","institution_ids":["https://openalex.org/I184558857"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052748715","display_name":"Clive Cheong Took","orcid":"https://orcid.org/0000-0001-6937-2329"},"institutions":[{"id":"https://openalex.org/I184558857","display_name":"Royal Holloway University of London","ror":"https://ror.org/04g2vpn86","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I184558857"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Clive Cheong Took","raw_affiliation_strings":["Royal Holloway University of London,Electronic Engineering Department,Egham,UK","Electronic Engineering Department, Royal Holloway University of London, Egham, UK"],"affiliations":[{"raw_affiliation_string":"Royal Holloway University of London,Electronic Engineering Department,Egham,UK","institution_ids":["https://openalex.org/I184558857"]},{"raw_affiliation_string":"Electronic Engineering Department, Royal Holloway University of London, Egham, UK","institution_ids":["https://openalex.org/I184558857"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004587843","display_name":"Saeid Sanei","orcid":"https://orcid.org/0000-0002-1446-5744"},"institutions":[{"id":"https://openalex.org/I52590639","display_name":"Nottingham Trent University","ror":"https://ror.org/04xyxjd90","country_code":"GB","type":"education","lineage":["https://openalex.org/I52590639"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Saeid Sanei","raw_affiliation_strings":["Nottingham Trent University,Computer Science Department,Nottingham,UK","Computer Science Department, Nottingham Trent University, Nottingham, UK"],"affiliations":[{"raw_affiliation_string":"Nottingham Trent University,Computer Science Department,Nottingham,UK","institution_ids":["https://openalex.org/I52590639"]},{"raw_affiliation_string":"Computer Science Department, Nottingham Trent University, Nottingham, UK","institution_ids":["https://openalex.org/I52590639"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5104194966"],"corresponding_institution_ids":["https://openalex.org/I184558857"],"apc_list":null,"apc_paid":null,"fwci":0.123,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.40113728,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"354","last_page":"358"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9993000030517578,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.998199999332428,"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/backpropagation","display_name":"Backpropagation","score":0.8528258800506592},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7230037450790405},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.7085356712341309},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6311650276184082},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5657097101211548},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.5508447289466858},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5136479735374451},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5011155605316162},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4612599313259125},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38461846113204956},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.15197604894638062}],"concepts":[{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.8528258800506592},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7230037450790405},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.7085356712341309},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6311650276184082},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5657097101211548},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.5508447289466858},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5136479735374451},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5011155605316162},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4612599313259125},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38461846113204956},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.15197604894638062},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ssp53291.2023.10207944","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ssp53291.2023.10207944","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE Statistical Signal Processing Workshop (SSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1849277567","https://openalex.org/W2058262254","https://openalex.org/W2117539524","https://openalex.org/W2194775991","https://openalex.org/W2243226955","https://openalex.org/W2961719374","https://openalex.org/W2964140963","https://openalex.org/W3198949520","https://openalex.org/W4246193833","https://openalex.org/W6637373629","https://openalex.org/W6732990564"],"related_works":["https://openalex.org/W2115605526","https://openalex.org/W3093883775","https://openalex.org/W1539246760","https://openalex.org/W2786746258","https://openalex.org/W4225893763","https://openalex.org/W2788727425","https://openalex.org/W2405196115","https://openalex.org/W2104893957","https://openalex.org/W4402471162","https://openalex.org/W2971074373"],"abstract_inverted_index":{"Image":[0],"filters":[1,19],"play":[2],"a":[3,29,64,80,123],"crucial":[4],"role":[5],"in":[6,73],"the":[7,15,31,37,46,51,57,85,101],"performance":[8],"of":[9,17,66,127],"convolutional":[10],"neural":[11],"networks":[12],"(CNNs).":[13],"Yet,":[14],"optimisation":[16],"those":[18],"tends":[20],"to":[21,44,69,83,118],"focus":[22],"solely":[23],"on":[24,56,90],"optimising":[25],"their":[26],"weights.":[27],"As":[28],"result,":[30],"machine":[32],"learning":[33],"practitioner":[34],"either":[35,91],"uses":[36],"standard":[38],"3\u00d73":[39],"filter":[40,47,53,86],"size":[41,48,54,87],"or":[42,94],"has":[43,62],"select":[45],"empirically,":[49],"as":[50],"optimal":[52,120],"depends":[55],"application":[58],"at":[59,122],"hand.":[60],"There":[61],"been":[63],"lack":[65],"serious":[67,103],"attempts":[68],"address":[70],"this":[71,76],"issue":[72],"CNNs.":[74],"To":[75],"end,":[77],"we":[78],"propose":[79],"novel":[81],"technique":[82,99],"learn":[84],"without":[88],"depending":[89],"gradient":[92],"descent":[93],"backpropagation.":[95],"We":[96],"compare":[97],"our":[98,111],"with":[100],"only":[102,110],"attempt":[104],"existing":[105],"and":[106],"show":[107],"that":[108],"not":[109],"method":[112],"performs":[113],"better,":[114],"but":[115],"also":[116],"converges":[117],"an":[119],"solution":[121],"much":[124],"smaller":[125],"number":[126],"training":[128],"iterations.":[129]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-12-21T23:12:01.093139","created_date":"2025-10-10T00:00:00"}