{"id":"https://openalex.org/W4220666040","doi":"https://doi.org/10.3390/sym14040658","title":"Improving Classification Performance of Fully Connected Layers by Fuzzy Clustering in Transformed Feature Space","display_name":"Improving Classification Performance of Fully Connected Layers by Fuzzy Clustering in Transformed Feature Space","publication_year":2022,"publication_date":"2022-03-24","ids":{"openalex":"https://openalex.org/W4220666040","doi":"https://doi.org/10.3390/sym14040658"},"language":"en","primary_location":{"id":"doi:10.3390/sym14040658","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym14040658","pdf_url":"https://www.mdpi.com/2073-8994/14/4/658/pdf?version=1648101249","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2073-8994/14/4/658/pdf?version=1648101249","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5080990305","display_name":"Tolga Ahmet Kalayc\u0131","orcid":"https://orcid.org/0000-0001-5706-6455"},"institutions":[{"id":"https://openalex.org/I48912391","display_name":"Istanbul Technical University","ror":"https://ror.org/059636586","country_code":"TR","type":"education","lineage":["https://openalex.org/I48912391"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Tolga Ahmet Kalayc\u0131","raw_affiliation_strings":["Department of Industrial Engineering, Istanbul Technical University, Ma\u00e7ka, \u0130stanbul 34367, Turkey"],"raw_orcid":"https://orcid.org/0000-0001-5706-6455","affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, Istanbul Technical University, Ma\u00e7ka, \u0130stanbul 34367, Turkey","institution_ids":["https://openalex.org/I48912391"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067978277","display_name":"Umut Asan","orcid":"https://orcid.org/0000-0002-0838-1421"},"institutions":[{"id":"https://openalex.org/I48912391","display_name":"Istanbul Technical University","ror":"https://ror.org/059636586","country_code":"TR","type":"education","lineage":["https://openalex.org/I48912391"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Umut Asan","raw_affiliation_strings":["Department of Industrial Engineering, Istanbul Technical University, Ma\u00e7ka, \u0130stanbul 34367, Turkey"],"raw_orcid":"https://orcid.org/0000-0002-0838-1421","affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, Istanbul Technical University, Ma\u00e7ka, \u0130stanbul 34367, Turkey","institution_ids":["https://openalex.org/I48912391"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5080990305"],"corresponding_institution_ids":["https://openalex.org/I48912391"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2227},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2227},"fwci":1.7063,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.84865959,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"14","issue":"4","first_page":"658","last_page":"658"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9977999925613403,"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/T10057","display_name":"Face and Expression Recognition","score":0.9977999925613403,"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":0.9955000281333923,"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":0.9940000176429749,"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":0.7825889587402344},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6926575899124146},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5855538845062256},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5658135414123535},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5215590000152588},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5177780389785767},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4972222149372101},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.4533020257949829},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.44053414463996887},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.43400418758392334},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.424960732460022},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.4211037755012512},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4154200851917267},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3870611786842346},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3496229648590088}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7825889587402344},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6926575899124146},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5855538845062256},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5658135414123535},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5215590000152588},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5177780389785767},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4972222149372101},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.4533020257949829},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.44053414463996887},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.43400418758392334},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.424960732460022},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.4211037755012512},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4154200851917267},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3870611786842346},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3496229648590088},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"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},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/sym14040658","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym14040658","pdf_url":"https://www.mdpi.com/2073-8994/14/4/658/pdf?version=1648101249","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:12f03c13fc9b403b951fba0c229f3d49","is_oa":true,"landing_page_url":"https://doaj.org/article/12f03c13fc9b403b951fba0c229f3d49","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":"Symmetry, Vol 14, Iss 4, p 658 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2073-8994/14/4/658/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/sym14040658","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry","raw_type":"Text"},{"id":"pmh:oai:polen.itu.edu.tr:11527/45237","is_oa":false,"landing_page_url":"https://hdl.handle.net/11527/45237","pdf_url":null,"source":{"id":"https://openalex.org/S4306400460","display_name":"Istanbul Technical University Academic Open Archive (Istanbul Technical University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I48912391","host_organization_name":"Istanbul Technical University","host_organization_lineage":["https://openalex.org/I48912391"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"}],"best_oa_location":{"id":"doi:10.3390/sym14040658","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym14040658","pdf_url":"https://www.mdpi.com/2073-8994/14/4/658/pdf?version=1648101249","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4220666040.pdf"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W1977741415","https://openalex.org/W2003649494","https://openalex.org/W2014098003","https://openalex.org/W2041917805","https://openalex.org/W2057028265","https://openalex.org/W2064395451","https://openalex.org/W2112802728","https://openalex.org/W2145901919","https://openalex.org/W2147944097","https://openalex.org/W2167638481","https://openalex.org/W2313243577","https://openalex.org/W2319017187","https://openalex.org/W2398788757","https://openalex.org/W2468221858","https://openalex.org/W2484215240","https://openalex.org/W2516797325","https://openalex.org/W2799612214","https://openalex.org/W2808691476","https://openalex.org/W2889922265","https://openalex.org/W2905810301","https://openalex.org/W2911008619","https://openalex.org/W2944339144","https://openalex.org/W3000978536","https://openalex.org/W3028396412","https://openalex.org/W3048485498","https://openalex.org/W3157558756","https://openalex.org/W3159532978","https://openalex.org/W3217736865","https://openalex.org/W4249131317","https://openalex.org/W6660778026","https://openalex.org/W6668502158"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W2130974462","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W4246352526","https://openalex.org/W2121910908","https://openalex.org/W915438175","https://openalex.org/W4230315250"],"abstract_inverted_index":{"Fully":[0],"connected":[1,103],"(FC)":[2],"layers":[3,21,46,104],"are":[4],"used":[5],"in":[6,82,123,168,201,214],"almost":[7],"all":[8],"neural":[9,18],"network":[10],"architectures":[11],"ranging":[12],"from":[13],"multilayer":[14],"perceptrons":[15],"to":[16,65,75,108,118,132,147,209],"deep":[17],"networks.":[19],"FC":[20,140,212],"allow":[22],"any":[23,32],"kind":[24],"of":[25,37,42,49,58,69,89,128,152,179],"symmetric/asymmetric":[26],"interaction":[27],"between":[28],"features":[29,155],"without":[30],"making":[31],"assumption":[33],"about":[34],"the":[35,38,55,67,87,120,124,129,133,139,149,153,159,172,177,180,196],"structure":[36,57,81],"data.":[39],"However,":[40],"success":[41,68],"convolutional":[43],"and":[44,47,77,156,203],"recursive":[45],"findings":[48],"many":[50],"studies":[51],"have":[52],"proven":[53],"that":[54,195],"intrinsic":[56,80],"a":[59,62,70,97,210],"dataset":[60,131],"holds":[61],"great":[63],"potential":[64],"improve":[66],"classification":[71,83,112,160,206],"problem.":[72],"Leveraging":[73],"clustering":[74,121,173],"explore":[76],"exploit":[78],"this":[79,93,143,169],"problems":[84],"has":[85],"been":[86],"subject":[88],"various":[90],"studies.":[91],"In":[92,142],"paper,":[94],"we":[95,145],"propose":[96],"new":[98],"training":[99,130],"pipeline":[100],"for":[101],"fully":[102],"which":[105],"enables":[106],"them":[107],"make":[109],"more":[110],"accurate":[111],"predictions.":[113],"The":[114,162],"proposed":[115,181,197],"method":[116,198],"aims":[117],"reflect":[119],"patterns":[122],"original":[125],"feature":[126,135],"space":[127,136],"transformed":[134],"created":[137],"by":[138],"layer.":[141],"way,":[144],"intend":[146],"enhance":[148],"representation":[150],"ability":[151],"extracted":[154],"accordingly":[157],"increase":[158],"accuracy.":[161],"Fuzzy":[163],"C-Means":[164],"algorithm":[165],"is":[166],"employed":[167],"study":[170],"as":[171],"tool.":[174],"To":[175],"evaluate":[176],"performance":[178],"method,":[182],"11":[183],"experiments":[184],"were":[185],"conducted":[186],"on":[187],"9":[188],"benchmark":[189],"UCI":[190],"datasets.":[191,216],"Empirical":[192],"results":[193],"show":[194],"works":[199],"well":[200],"practice":[202],"gives":[204],"higher":[205],"accuracies":[207],"compared":[208],"regular":[211],"layer":[213],"most":[215]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":5}],"updated_date":"2026-07-30T17:31:21.811387","created_date":"2025-10-10T00:00:00"}
