{"id":"https://openalex.org/W4408791796","doi":"https://doi.org/10.1109/access.2025.3554395","title":"Unbalancing Datasets to Enhance CNN Models Learnability: A Class-Wise Metrics-Based Closed-Loop Strategy Proposal","display_name":"Unbalancing Datasets to Enhance CNN Models Learnability: A Class-Wise Metrics-Based Closed-Loop Strategy Proposal","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4408791796","doi":"https://doi.org/10.1109/access.2025.3554395"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3554395","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3554395","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3554395","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053289037","display_name":"Somayeh Shahrabadi","orcid":null},"institutions":[{"id":"https://openalex.org/I99682543","display_name":"University of Minho","ror":"https://ror.org/037wpkx04","country_code":"PT","type":"education","lineage":["https://openalex.org/I99682543"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Somayeh Shahrabadi","raw_affiliation_strings":["Department of Informatics, University of Minho, Braga, Portugal"],"raw_orcid":"https://orcid.org/0009-0002-0239-0471","affiliations":[{"raw_affiliation_string":"Department of Informatics, University of Minho, Braga, Portugal","institution_ids":["https://openalex.org/I99682543"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016100261","display_name":"Victor Alves","orcid":"https://orcid.org/0000-0003-1819-7051"},"institutions":[{"id":"https://openalex.org/I99682543","display_name":"University of Minho","ror":"https://ror.org/037wpkx04","country_code":"PT","type":"education","lineage":["https://openalex.org/I99682543"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Victor Alves","raw_affiliation_strings":["Department of Informatics, University of Minho, Braga, Portugal"],"raw_orcid":"https://orcid.org/0000-0003-1819-7051","affiliations":[{"raw_affiliation_string":"Department of Informatics, University of Minho, Braga, Portugal","institution_ids":["https://openalex.org/I99682543"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020489061","display_name":"Emanuel Peres","orcid":"https://orcid.org/0000-0001-5669-7976"},"institutions":[{"id":"https://openalex.org/I155381812","display_name":"University of Tr\u00e1s-os-Montes and Alto Douro","ror":"https://ror.org/03qc8vh97","country_code":"PT","type":"education","lineage":["https://openalex.org/I155381812"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Emanuel Peres","raw_affiliation_strings":["Department of Engineering, School of Sciences and Technology, University of Trás-os-Montes e Alto Douro, Vila Real, Portugal"],"raw_orcid":"https://orcid.org/0000-0001-5669-7976","affiliations":[{"raw_affiliation_string":"Department of Engineering, School of Sciences and Technology, University of Trás-os-Montes e Alto Douro, Vila Real, Portugal","institution_ids":["https://openalex.org/I155381812"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060198162","display_name":"Raul Morais","orcid":"https://orcid.org/0000-0003-2440-9153"},"institutions":[{"id":"https://openalex.org/I155381812","display_name":"University of Tr\u00e1s-os-Montes and Alto Douro","ror":"https://ror.org/03qc8vh97","country_code":"PT","type":"education","lineage":["https://openalex.org/I155381812"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Raul Morais Dos Santos","raw_affiliation_strings":["Department of Engineering, School of Sciences and Technology, University of Trás-os-Montes e Alto Douro, Vila Real, Portugal"],"raw_orcid":"https://orcid.org/0000-0003-2440-9153","affiliations":[{"raw_affiliation_string":"Department of Engineering, School of Sciences and Technology, University of Trás-os-Montes e Alto Douro, Vila Real, Portugal","institution_ids":["https://openalex.org/I155381812"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052054587","display_name":"Telmo Ad\u00e3o","orcid":"https://orcid.org/0000-0002-2727-0014"},"institutions":[{"id":"https://openalex.org/I99682543","display_name":"University of Minho","ror":"https://ror.org/037wpkx04","country_code":"PT","type":"education","lineage":["https://openalex.org/I99682543"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Telmo Ad\u00e3o","raw_affiliation_strings":["ALGORITMI Research Centre/LASI, University of Minho, Guimarães, Portugal"],"raw_orcid":"https://orcid.org/0000-0002-2727-0014","affiliations":[{"raw_affiliation_string":"ALGORITMI Research Centre/LASI, University of Minho, Guimarães, Portugal","institution_ids":["https://openalex.org/I99682543"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.396,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.82783259,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"13","issue":null,"first_page":"57485","last_page":"57503"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9333999752998352,"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"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9333999752998352,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9203000068664551,"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/learnability","display_name":"Learnability","score":0.9342247247695923},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7911109924316406},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.6152253150939941},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4892549514770508},{"id":"https://openalex.org/keywords/loop","display_name":"Loop (graph theory)","score":0.4177309274673462},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39893800020217896},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36462533473968506},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.35277315974235535},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11558297276496887}],"concepts":[{"id":"https://openalex.org/C2777723229","wikidata":"https://www.wikidata.org/wiki/Q4367921","display_name":"Learnability","level":2,"score":0.9342247247695923},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7911109924316406},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.6152253150939941},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4892549514770508},{"id":"https://openalex.org/C184670325","wikidata":"https://www.wikidata.org/wiki/Q512604","display_name":"Loop (graph theory)","level":2,"score":0.4177309274673462},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39893800020217896},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36462533473968506},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.35277315974235535},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11558297276496887},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3554395","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3554395","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:927585eed38843b5bc1edc46123f840e","is_oa":true,"landing_page_url":"https://doaj.org/article/927585eed38843b5bc1edc46123f840e","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 Access, Vol 13, Pp 57485-57503 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3554395","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3554395","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.4699999988079071,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4302791369","https://openalex.org/W2951285859","https://openalex.org/W2766040214","https://openalex.org/W72092541","https://openalex.org/W37360785","https://openalex.org/W1973394166","https://openalex.org/W180475243","https://openalex.org/W2098466205","https://openalex.org/W1966604104","https://openalex.org/W2066099325"],"abstract_inverted_index":{"Developing":[0],"deep":[1],"learning":[2,203],"models":[3,191,238],"often":[4,76],"involves":[5],"working":[6],"with":[7,29,134,192,252],"balanced":[8],"datasets.":[9,258],"However,":[10],"in":[11,132,229],"real-world":[12],"scenarios,":[13],"class":[14,68,307],"equilibrium":[15],"is":[16,67,71],"rarely":[17],"observed.":[18],"To":[19,108,165],"address":[20,109],"this,":[21],"oversampling":[22],"and":[23,32,75,89,129,143,158,169,205,211,275,288,311,324],"undersampling":[24],"techniques":[25],"are":[26,44],"commonly":[27],"employed,":[28],"appropriate":[30],"monitoring":[31],"countermeasures":[33],"to":[34,52,73,125,161,180,255,318],"mitigate":[35,162],"the":[36,79,104,123,135,233,237,256,263,279,320],"risk":[37],"of":[38,64,81,106,174,232,273],"overfitting.":[39],"Yet,":[40],"even":[41],"when":[42],"datasets":[43,177],"balanced,":[45],"they":[46],"can":[47,98],"still":[48],"introduce":[49],"biases,":[50],"leading":[51],"better":[53],"classification":[54],"performance":[55,128,146,323],"for":[56,277],"certain":[57],"classes":[58,149],"over":[59,313],"others.":[60],"One":[61],"significant":[62],"cause":[63],"such":[65,93],"biases":[66],"underrepresentation,":[69],"which":[70],"challenging":[72],"control":[74],"arises":[77],"from":[78],"acquisition":[80],"uneven":[82],"feature":[83],"distributions":[84],"influenced":[85],"by":[86,150],"endogenous":[87],"factors":[88],"environmental":[90],"conditions.":[91],"In":[92,218],"cases,":[94],"random":[95],"data":[96,152],"augmentation":[97,153,290],"inadvertently":[99],"amplify":[100],"these":[101,188],"discrepancies,":[102],"exacerbating":[103],"issue":[105],"underrepresentation.":[107,164],"this":[110,112,219],"challenge,":[111],"paper":[113],"proposes":[114],"a":[115,172,293],"metrics-based":[116],"closed-loop":[117],"(MbCL)":[118],"approach":[119],"that":[120,262,286],"strategically":[121],"unbalances":[122],"dataset":[124],"enhance":[126],"class-wise":[127],"model":[130,145],"generalization":[131],"line":[133],"training":[136,228,257],"process.":[137],"The":[138,259],"proposed":[139,264],"method":[140],"iteratively":[141],"adjusts":[142],"improves":[144],"across":[147,184],"different":[148,197,248],"employing":[151],"techniques,":[154],"including":[155,196,305],"both":[156,278],"classical":[157],"GAN-based":[159,289],"methods,":[160],"classes\u2019":[163],"compare":[166],"regular":[167],"(linear)":[168],"MbCL-based":[170],"approaches,":[171],"couple":[173],"contextually":[175],"distinct":[176],"were":[178,208,239,316],"considered":[179],"broaden":[181],"consistency":[182],"analysis":[183],"some":[185],"diversity.":[186],"Using":[187],"datasets,":[189],"72":[190],"varying":[193],"configurations":[194],"\u2013":[195,207],"convolutional":[198],"neural":[199],"network":[200],"architectures,":[201],"initial":[202],"rates,":[204],"optimizers":[206],"initially":[209],"trained":[210],"then":[212],"evaluated":[213],"against":[214],"imagery":[215],"test":[216],"sets.":[217],"first":[220],"assessment,":[221],"MbCL":[222,265],"methods":[223,266],"matched":[224],"or":[225],"outperformed":[226,268],"linear":[227,269],"approximately":[230],"85%":[231],"cases.":[234],"Additionally,":[235],"all":[236],"tested":[240],"on":[241,296],"an":[242],"external":[243],"image":[244],"set":[245],"acquired":[246],"under":[247],"contextual":[249],"conditions":[250],"but":[251],"matching":[253],"labels":[254],"results":[260],"showed":[261],"consistently":[267],"training,":[270],"achieving":[271],"top-accuracies":[272],"32%":[274],"72%":[276],"encompassed":[280],"dataset-related":[281],"contexts,":[282],"therefore,":[283],"also":[284],"indicating":[285],"classic":[287],"approaches":[291],"had":[292],"positive":[294],"impact":[295],"inference":[297],"performances":[298],"as":[299],"resampling":[300],"strategies.":[301],"Furthermore,":[302],"complementary":[303],"indicators,":[304],"gradient-weighted":[306],"activation":[308],"mapping":[309],"(Grad-CAM)":[310],"intersection":[312],"union":[314],"(IoU),":[315],"analyzed":[317],"explore":[319],"relationship":[321],"between":[322],"visualizable":[325],"features.":[326]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}