{"id":"https://openalex.org/W7117965826","doi":"https://doi.org/10.1109/enc68268.2025.11311921","title":"Assessing the Impact of Network Regularizers on the Performance of Convolutional Neural Network Architectures Evolved by DeepGA","display_name":"Assessing the Impact of Network Regularizers on the Performance of Convolutional Neural Network Architectures Evolved by DeepGA","publication_year":2025,"publication_date":"2025-11-10","ids":{"openalex":"https://openalex.org/W7117965826","doi":"https://doi.org/10.1109/enc68268.2025.11311921"},"language":null,"primary_location":{"id":"doi:10.1109/enc68268.2025.11311921","is_oa":false,"landing_page_url":"https://doi.org/10.1109/enc68268.2025.11311921","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Mexican International Conference on Computer Science (ENC)","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/A5092110612","display_name":"Jes\u00fas-Arnulfo Barradas-Palmeros","orcid":"https://orcid.org/0009-0008-1187-4981"},"institutions":[{"id":"https://openalex.org/I4210131846","display_name":"Artificial Intelligence Research Institute","ror":"https://ror.org/03c0ach84","country_code":"ES","type":"facility","lineage":["https://openalex.org/I134820265","https://openalex.org/I4210131846"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Jes\u00fas-Arnulfo Barradas-Palmeros","raw_affiliation_strings":["Artificial Intelligence Research Institute"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Research Institute","institution_ids":["https://openalex.org/I4210131846"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058469717","display_name":"Efr\u00e9n Mezura\u2010Montes","orcid":"https://orcid.org/0000-0002-1565-5267"},"institutions":[{"id":"https://openalex.org/I4210131846","display_name":"Artificial Intelligence Research Institute","ror":"https://ror.org/03c0ach84","country_code":"ES","type":"facility","lineage":["https://openalex.org/I134820265","https://openalex.org/I4210131846"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Efr\u00e9n Mezura-Montes","raw_affiliation_strings":["Artificial Intelligence Research Institute"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Research Institute","institution_ids":["https://openalex.org/I4210131846"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087996636","display_name":"H\u00e9ctor-Gabriel Acosta-Mesa","orcid":null},"institutions":[{"id":"https://openalex.org/I4210131846","display_name":"Artificial Intelligence Research Institute","ror":"https://ror.org/03c0ach84","country_code":"ES","type":"facility","lineage":["https://openalex.org/I134820265","https://openalex.org/I4210131846"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"H\u00e9ctor-Gabriel Acosta-Mesa","raw_affiliation_strings":["Artificial Intelligence Research Institute"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Research Institute","institution_ids":["https://openalex.org/I4210131846"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121797248","display_name":"Carlos-Alberto L\u00f3pez-Herrera","orcid":null},"institutions":[{"id":"https://openalex.org/I4210131846","display_name":"Artificial Intelligence Research Institute","ror":"https://ror.org/03c0ach84","country_code":"ES","type":"facility","lineage":["https://openalex.org/I134820265","https://openalex.org/I4210131846"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Carlos-Alberto L\u00f3pez-Herrera","raw_affiliation_strings":["Artificial Intelligence Research Institute"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Research Institute","institution_ids":["https://openalex.org/I4210131846"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121756297","display_name":"Francisco-Javier Hern\u00e1ndez-Somohano","orcid":null},"institutions":[{"id":"https://openalex.org/I3129323158","display_name":"Universidad de Xalapa","ror":"https://ror.org/02aneaq95","country_code":"MX","type":"education","lineage":["https://openalex.org/I3129323158"]},{"id":"https://openalex.org/I26166359","display_name":"El Colegio de Veracruz","ror":"https://ror.org/05s1yqk76","country_code":"MX","type":"education","lineage":["https://openalex.org/I26166359"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Francisco-Javier Hern\u00e1ndez-Somohano","raw_affiliation_strings":["School of Statistics and Informatics, University of Veracruz,Xalapa,Mexico"],"affiliations":[{"raw_affiliation_string":"School of Statistics and Informatics, University of Veracruz,Xalapa,Mexico","institution_ids":["https://openalex.org/I3129323158","https://openalex.org/I26166359"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5092110612"],"corresponding_institution_ids":["https://openalex.org/I4210131846"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.65414733,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.5935999751091003,"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":0.5935999751091003,"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":0.11420000344514847,"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":0.03060000017285347,"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/overfitting","display_name":"Overfitting","score":0.809499979019165},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.670199990272522},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6557000279426575},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5218999981880188},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.4765999913215637},{"id":"https://openalex.org/keywords/dropout","display_name":"Dropout (neural networks)","score":0.4603999853134155},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42410001158714294},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4203000068664551},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4196000099182129}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.809499979019165},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7684999704360962},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7197999954223633},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6998000144958496},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.670199990272522},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6557000279426575},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5218999981880188},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.4765999913215637},{"id":"https://openalex.org/C2776145597","wikidata":"https://www.wikidata.org/wiki/Q25339462","display_name":"Dropout (neural networks)","level":2,"score":0.4603999853134155},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42410001158714294},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4203000068664551},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4196000099182129},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.40849998593330383},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.40450000762939453},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4018999934196472},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.37860000133514404},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.36320000886917114},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.35929998755455017},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.3133000135421753},{"id":"https://openalex.org/C202269582","wikidata":"https://www.wikidata.org/wiki/Q2644277","display_name":"Complementarity (molecular biology)","level":2,"score":0.30550000071525574},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.3000999987125397},{"id":"https://openalex.org/C2944601119","wikidata":"https://www.wikidata.org/wiki/Q43744058","display_name":"Residual neural network","level":3,"score":0.2870999872684479},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.2718999981880188},{"id":"https://openalex.org/C5465570","wikidata":"https://www.wikidata.org/wiki/Q5326898","display_name":"Early stopping","level":3,"score":0.2653000056743622},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.2581999897956848}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/enc68268.2025.11311921","is_oa":false,"landing_page_url":"https://doi.org/10.1109/enc68268.2025.11311921","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Mexican International Conference on Computer Science (ENC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322937","display_name":"Universidad Veracruzana","ror":"https://ror.org/03efxn362"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1936750108","https://openalex.org/W2183341477","https://openalex.org/W2887063112","https://openalex.org/W2963946985","https://openalex.org/W2998508940","https://openalex.org/W3037340973","https://openalex.org/W3164008977","https://openalex.org/W3168997536","https://openalex.org/W3178493357","https://openalex.org/W3192682950","https://openalex.org/W4206569030","https://openalex.org/W4378220234","https://openalex.org/W4383103612","https://openalex.org/W4385342469","https://openalex.org/W4399715157","https://openalex.org/W4401700017","https://openalex.org/W4403294840","https://openalex.org/W4406113408","https://openalex.org/W4408238307","https://openalex.org/W4412964393"],"related_works":[],"abstract_inverted_index":{"Overfitting":[0],"is":[1,47],"a":[2,82],"persistent":[3],"problem":[4],"in":[5,116,138,143,164,179,186],"Convolutional":[6],"Neural":[7,53],"Networks":[8],"(CNNs)":[9],"that":[10,58,120],"limits":[11],"the":[12,24,30,42,69,75,100,121,139,148,152,157,165,173,188],"model's":[13,189],"generalization":[14],"capabilities.":[15],"To":[16],"counteract":[17],"overfitting,":[18],"network":[19,61],"regularizers":[20,155,178],"are":[21,99,112],"incorporated":[22],"into":[23,172],"training":[25,88,166],"process.":[26],"In":[27],"this":[28],"work,":[29],"impact":[31],"of":[32,78,85,154,177],"applying":[33],"different":[34],"regularization":[35],"strategies":[36],"to":[37,161],"CNN":[38,181],"architectures":[39],"evolved":[40,79,180],"with":[41],"Deep":[43],"Genetic":[44],"Algorithm":[45],"(DeepGA)":[46],"studied.":[48],"DeepGA":[49],"follows":[50],"an":[51,162],"Evolutionary":[52],"Architecture":[54],"Search":[55],"(ENAS)":[56],"process":[57],"considers":[59],"both":[60],"performance":[62,86],"and":[63,71,87,95,107,111,115,130,175],"complexity.":[64],"Experiments":[65],"were":[66],"conducted":[67],"on":[68],"CIFAR-100":[70],"CIFAR-10":[72],"datasets":[73],"using":[74],"same":[76],"set":[77],"architectures,":[80,182],"allowing":[81],"controlled":[83],"comparison":[84],"cost.":[89],"Random":[90],"Erasing":[91],"(RE),":[92],"Dropout":[93],"(DO),":[94],"Label":[96],"Smoothing":[97],"(LS)":[98],"selected":[101],"regularizers,":[102],"which":[103],"involve":[104],"input,":[105],"internal,":[106],"label":[108],"regularization,":[109],"respectively,":[110],"applied":[113],"individually":[114],"combination.":[117],"Results":[118],"show":[119],"combined":[122],"configurations,":[123],"especially":[124],"<tex":[125,131],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[126,132],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\mathbf{R":[127,133],"E}+\\mathbf{D":[128,134],"O}$</tex>":[129],"O}+\\mathbf{L":[135],"S}$</tex>,":[136],"resulted":[137],"most":[140],"significant":[141],"improvement":[142],"test":[144],"accuracy,":[145],"significantly":[146],"outperforming":[147],"non-regularized":[149],"baseline.":[150],"Nonetheless,":[151],"use":[153],"expanded":[156],"computational":[158],"cost":[159],"due":[160],"increase":[163],"time.":[167],"The":[168],"findings":[169],"provide":[170],"insights":[171],"role":[174],"interaction":[176],"highlighting":[183],"their":[184],"benefits":[185],"boosting":[187],"performance.":[190]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2026-01-02T00:00:00"}
