{"id":"https://openalex.org/W4400811535","doi":"https://doi.org/10.1109/ccict62777.2024.00083","title":"Face Classification Using Stacking Ensemble Learning","display_name":"Face Classification Using Stacking Ensemble Learning","publication_year":2024,"publication_date":"2024-04-19","ids":{"openalex":"https://openalex.org/W4400811535","doi":"https://doi.org/10.1109/ccict62777.2024.00083"},"language":"en","primary_location":{"id":"doi:10.1109/ccict62777.2024.00083","doi":"https://doi.org/10.1109/ccict62777.2024.00083","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ccict62777.2024.00083","pdf_url":null,"source":{"id":"https://openalex.org/S4363608536","display_name":"International Conference on Computational Intelligence and Communication Technologies (CCICT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 Sixth International Conference on Computational Intelligence and Communication Technologies (CCICT)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5065377007","display_name":"Aditi Arora","orcid":"https://orcid.org/0000-0002-2314-8900","observed_orcids":["https://orcid.org/0000-0002-2314-8900"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aditi Arora","raw_affiliation_strings":["ABESEC,Department of CSE,Ghaziabad,UP,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ABESEC,Department of CSE,Ghaziabad,UP,India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039460172","display_name":"Indu Malik","orcid":"https://orcid.org/0000-0003-3080-001X","observed_orcids":["https://orcid.org/0000-0003-3080-001X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Indu Malik","raw_affiliation_strings":["ABESEC,Department of CSE,Ghaziabad,UP,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ABESEC,Department of CSE,Ghaziabad,UP,India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113296058","display_name":"Aanchal Gupta","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aanchal Gupta","raw_affiliation_strings":["ABESEC,Department of CSE,Ghaziabad,UP,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ABESEC,Department of CSE,Ghaziabad,UP,India","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Bhavya Jindal","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bhavya Jindal","raw_affiliation_strings":["ABESEC,Department of CSE,Ghaziabad,UP,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ABESEC,Department of CSE,Ghaziabad,UP,India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113296060","display_name":"Gaurisha Gupta","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gaurisha Gupta","raw_affiliation_strings":["ABESEC,Department of CSE,Ghaziabad,UP,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ABESEC,Department of CSE,Ghaziabad,UP,India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"498","last_page":"505"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9731000065803528,"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":0.9731000065803528,"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/T11448","display_name":"Face recognition and analysis","score":0.022199999541044235,"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/T10828","display_name":"Biometric Identification and Security","score":0.0034000000450760126,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/face-recognition","display_name":"face recognition","score":0.7609999775886536},{"id":"https://openalex.org/keywords/face-identification","display_name":"face identification","score":0.7710000276565552},{"id":"https://openalex.org/keywords/stacking-ensemble","display_name":"stacking ensemble","score":0.8989999890327454},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"principal component analysis","score":0.8759999871253967},{"id":"https://openalex.org/keywords/biometric-authentication","display_name":"biometric authentication","score":0.8240000009536743},{"id":"https://openalex.org/keywords/eye-detection","display_name":"eye detection","score":0.8420000076293945},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"feature extraction","score":0.3610000014305115},{"id":"https://openalex.org/keywords/classifier-comparison","display_name":"classifier comparison","score":0.36800000071525574}],"concepts":[{"id":"https://openalex.org/C33347731","wikidata":"https://www.wikidata.org/wiki/Q285210","display_name":"Stacking","level":2,"score":0.8131192922592163},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.689003050327301},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6327481269836426},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.6055031418800354},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.5881639719009399},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48355576395988464},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.4240204393863678},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4142269492149353},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0771033763885498},{"id":"https://openalex.org/C46141821","wikidata":"https://www.wikidata.org/wiki/Q209402","display_name":"Nuclear magnetic resonance","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccict62777.2024.00083","doi":"https://doi.org/10.1109/ccict62777.2024.00083","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ccict62777.2024.00083","pdf_url":null,"source":{"id":"https://openalex.org/S4363608536","display_name":"International Conference on Computational Intelligence and Communication Technologies (CCICT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 Sixth International Conference on Computational Intelligence and Communication Technologies (CCICT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W1881452810","https://openalex.org/W2784158897","https://openalex.org/W2887231075","https://openalex.org/W3020972774","https://openalex.org/W3041486090","https://openalex.org/W3092247442","https://openalex.org/W3201016768"],"related_works":["https://openalex.org/W4403675294","https://openalex.org/W3081976054","https://openalex.org/W2354652271","https://openalex.org/W4387348770","https://openalex.org/W1592307416","https://openalex.org/W2114341012","https://openalex.org/W2896061806","https://openalex.org/W2990587183","https://openalex.org/W4214596492","https://openalex.org/W4409734017"],"abstract_inverted_index":{"Developing":[0],"a":[1,23,26,30,37,46,65,114],"high-level":[2],"automated":[3],"security":[4,20,34],"system":[5,68,108,173],"for":[6,84],"identification/authentication":[7],"has":[8],"long":[9],"been":[10],"an":[11,176],"active":[12],"research":[13],"subject":[14],"in":[15,49,89,175],"practically":[16],"all":[17],"fields.":[18],"Traditional":[19],"systems":[21,35],"utilize":[22],"key":[24],"or":[25,40,154,178],"password":[27],"to":[28],"secure":[29],"process/product,":[31],"whereas":[32],"biometric":[33],"use":[36],"person\u2019s":[38],"physical":[39],"behavioral":[41],"attributes.":[42],"Face":[43,119],"patterns":[44],"play":[45],"significant":[47],"part":[48],"several":[50],"potential":[51],"recognition/authentication":[52],"applications":[53],"because":[54],"of":[55,144,168,208],"their":[56],"uniqueness,":[57],"universality,":[58],"dependability,":[59],"and":[60,74,100,111,128,232],"stability.":[61],"This":[62],"study":[63,91],"provides":[64],"face":[66,77,85,188],"identification":[67],"that":[69,92,141,165],"starts":[70],"with":[71,76,99,197],"eye":[72],"detection":[73],"ends":[75],"image":[78],"recognition.":[79],"AN":[80],"ensemble":[81,172],"stacking":[82,171],"approach":[83],"classification":[86],"is":[87,109,123,133,151,199,202],"presented":[88],"this":[90],"combines":[93],"various":[94],"Machine":[95,223],"learning":[96],"(ML)":[97],"algorithms":[98],"without":[101,159],"Principal":[102],"Component":[103],"Analysis":[104],"(PCA).":[105],"The":[106,121,138,161],"proposed":[107,191],"trained":[110],"tested":[112],"on":[113,152,203],"well-known":[115],"publically":[116],"available":[117],"Olivetti":[118,187],"Dataset.":[120],"dataset":[122,131],"split":[124],"into":[125],"75%":[126],"train":[127],"25%":[129],"test":[130],"which":[132,201],"also":[134,163],"transformed":[135],"using":[136],"PCA.":[137,160],"results":[139,174],"show":[140],"the":[142,157,166,169,182,190,206,209],"accuracy":[143,196,207],"each":[145],"base":[146,184,211],"model":[147],"having":[148],"PCA":[149,198],"data":[150],"par":[153],"better":[155,179],"than":[156,181,205],"one":[158],"paper":[162],"proves":[164],"performance":[167,180],"new":[170],"average":[177,204],"other":[183,210],"models.":[185],"For":[186],"dataset,":[189],"Stacked":[192],"Ensemble":[193],"Learning":[194],"model\u2019s":[195],"94%,":[200],"models,":[212],"including":[213],"Neural":[214],"Network":[215],"(NN)":[216],"(100%),":[217],"Random":[218],"Forest":[219],"(92%),":[220],"Support":[221],"Vector":[222],"(SVM)(96%),":[224],"Gaussian":[225],"Naives":[226],"Bayes(81%),":[227],"K-Nearest":[228],"Neighbour":[229],"(KNN)":[230],"(89%),":[231],"Logistic":[233],"Regression":[234],"(LR)":[235],"(97%)":[236],"respectively.":[237]},"counts_by_year":[],"updated_date":"2026-10-05T09:50:58.205359","created_date":"2024-07-20T00:00:00"}
