{"id":"https://openalex.org/W4385482355","doi":"https://doi.org/10.1109/ecai58194.2023.10194193","title":"Feature selection using genetic algorithms for improving accuracy in image classification tasks","display_name":"Feature selection using genetic algorithms for improving accuracy in image classification tasks","publication_year":2023,"publication_date":"2023-06-29","ids":{"openalex":"https://openalex.org/W4385482355","doi":"https://doi.org/10.1109/ecai58194.2023.10194193"},"language":"en","primary_location":{"id":"doi:10.1109/ecai58194.2023.10194193","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ecai58194.2023.10194193","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 15th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)","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/A5092016185","display_name":"Andrei Dug\u0103e\u0219escu","orcid":null},"institutions":[{"id":"https://openalex.org/I61641377","display_name":"Universitatea Na\u021bional\u0103 de \u0218tiin\u021b\u0103 \u0219i Tehnologie Politehnica Bucure\u0219ti","ror":"https://ror.org/0558j5q12","country_code":"RO","type":"education","lineage":["https://openalex.org/I61641377"]}],"countries":["RO"],"is_corresponding":true,"raw_author_name":"Andrei Dugaesescu","raw_affiliation_strings":["University Politehnica of Bucharest,Faculty of Automatic Control and Computers,Bucharest,Romania","Faculty of Automatic Control and Computers, University Politehnica of Bucharest, Bucharest, Romania"],"affiliations":[{"raw_affiliation_string":"University Politehnica of Bucharest,Faculty of Automatic Control and Computers,Bucharest,Romania","institution_ids":["https://openalex.org/I61641377"]},{"raw_affiliation_string":"Faculty of Automatic Control and Computers, University Politehnica of Bucharest, Bucharest, Romania","institution_ids":["https://openalex.org/I61641377"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091502453","display_name":"David-Traian Iancu","orcid":"https://orcid.org/0009-0002-0846-6844"},"institutions":[{"id":"https://openalex.org/I61641377","display_name":"Universitatea Na\u021bional\u0103 de \u0218tiin\u021b\u0103 \u0219i Tehnologie Politehnica Bucure\u0219ti","ror":"https://ror.org/0558j5q12","country_code":"RO","type":"education","lineage":["https://openalex.org/I61641377"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"David-Traian Iancu","raw_affiliation_strings":["University Politehnica of Bucharest,Faculty of Automatic Control and Computers,Bucharest,Romania","Faculty of Automatic Control and Computers, University Politehnica of Bucharest, Bucharest, Romania"],"affiliations":[{"raw_affiliation_string":"University Politehnica of Bucharest,Faculty of Automatic Control and Computers,Bucharest,Romania","institution_ids":["https://openalex.org/I61641377"]},{"raw_affiliation_string":"Faculty of Automatic Control and Computers, University Politehnica of Bucharest, Bucharest, Romania","institution_ids":["https://openalex.org/I61641377"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5092016185"],"corresponding_institution_ids":["https://openalex.org/I61641377"],"apc_list":null,"apc_paid":null,"fwci":0.3491,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.64444657,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"01","last_page":"06"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9988999962806702,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9988999962806702,"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":0.9968000054359436,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9911999702453613,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.81759113073349},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7195837497711182},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6970988512039185},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6126577854156494},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6109737753868103},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5993319153785706},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5758456587791443},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5755141377449036},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5137325525283813},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5034813284873962},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.4476524591445923},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.43670064210891724},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.42217516899108887},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3392454981803894},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.15948018431663513}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.81759113073349},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7195837497711182},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6970988512039185},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6126577854156494},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6109737753868103},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5993319153785706},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5758456587791443},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5755141377449036},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5137325525283813},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5034813284873962},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4476524591445923},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.43670064210891724},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.42217516899108887},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3392454981803894},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.15948018431663513},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ecai58194.2023.10194193","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ecai58194.2023.10194193","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 15th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1995806857","https://openalex.org/W2015870870","https://openalex.org/W2194775991","https://openalex.org/W2537453289","https://openalex.org/W2626182487","https://openalex.org/W2963912358","https://openalex.org/W3118608800","https://openalex.org/W4212817109"],"related_works":["https://openalex.org/W4296209631","https://openalex.org/W3097449145","https://openalex.org/W2561617217","https://openalex.org/W2355801475","https://openalex.org/W4206659427","https://openalex.org/W2170062176","https://openalex.org/W2148135840","https://openalex.org/W2005234362","https://openalex.org/W1997235926","https://openalex.org/W2565656575"],"abstract_inverted_index":{"Feature":[0],"selection":[1,63,107,156],"can":[2,50,79],"be":[3,51,175],"an":[4,121],"effective":[5],"tool":[6],"for":[7,35,39,86],"increasing":[8],"the":[9,18,37,40,54,67,74,87,91,100,116,126,145,155,161,171,180,188,195],"robustness":[10],"and":[11,96,144],"predictive":[12],"accuracy":[13],"of":[14,20,43,56,93,105,130,157,163,190,197],"classifiers,":[15],"especially":[16],"in":[17,53,90,137,179,194],"presence":[19],"noisy":[21],"features":[22,127],"or":[23],"when":[24,81],"their":[25],"dimensionality":[26],"is":[27],"high.":[28],"Genetic":[29],"algorithms":[30],"(GA)":[31],"lend":[32],"themselves":[33],"well":[34,119],"optimizing":[36],"search":[38],"best":[41],"subset":[42],"features.":[44,200],"This":[45],"paper":[46],"present":[47],"how":[48],"GA":[49,165],"integrated":[52],"training":[55,115],"neural":[57,133],"networks":[58],"(NNs)":[59],"as":[60,109,118,120,166],"a":[61,77,110,131,164,167,192],"feature":[62,106,168],"step":[64],"to":[65,152],"increase":[66],"model":[68,154],"performance.":[69],"The":[70],"reported":[71],"experiments":[72],"cover":[73],"effect":[75],"such":[76,191],"technique":[78],"have":[80],"confronted":[82],"with":[83,139],"various":[84],"sizes":[85],"trained":[88],"NN":[89],"context":[92,196],"both":[94,108],"harder":[95],"easier":[97],"datasets.":[98],"Moreover,":[99],"experimental":[101],"setups":[102],"make":[103],"use":[104],"traditional":[111],"pre-processing":[112],"step,":[113],"before":[114],"NN,":[117],"intermediary":[122],"processing":[123],"layer":[124],"between":[125],"extractor":[128],"part":[129],"convolutional":[132],"network":[134],"(CNN),":[135],"used":[136],"conjunction":[138],"more":[140],"conventional":[141],"statistical":[142],"features,":[143,158],"classification":[146],"head.":[147],"Although":[148],"CNNs":[149],"are":[150],"known":[151],"inherently":[153],"meaning":[159],"that":[160],"impact":[162],"selector":[169],"after":[170],"CNN":[172],"backbone":[173],"could":[174],"inhibited,":[176],"marginal":[177],"improvements":[178],"final":[181],"performance":[182],"still":[183],"show":[184],"meaningful":[185],"insight":[186],"into":[187],"working":[189],"classifier,":[193],"managing":[198],"relevant":[199]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
