{"id":"https://openalex.org/W7130568396","doi":"https://doi.org/10.1109/ictc66702.2025.11388431","title":"Rethinking GAN-Augmented Data: A Case Study on Leaf-GAN for Tomato Leaf Disease Classification","display_name":"Rethinking GAN-Augmented Data: A Case Study on Leaf-GAN for Tomato Leaf Disease Classification","publication_year":2025,"publication_date":"2025-10-14","ids":{"openalex":"https://openalex.org/W7130568396","doi":"https://doi.org/10.1109/ictc66702.2025.11388431"},"language":null,"primary_location":{"id":"doi:10.1109/ictc66702.2025.11388431","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ictc66702.2025.11388431","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 16th International Conference on Information and Communication Technology Convergence (ICTC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5126439480","display_name":"Prudhvi Sai Mandalapu","orcid":null},"institutions":[{"id":"https://openalex.org/I31419693","display_name":"Kyungpook National University","ror":"https://ror.org/040c17130","country_code":"KR","type":"education","lineage":["https://openalex.org/I31419693"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Prudhvi Sai Mandalapu","raw_affiliation_strings":["Kyungpook National University,Department of Artificial Intelligence,Daegu,South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kyungpook National University,Department of Artificial Intelligence,Daegu,South Korea","institution_ids":["https://openalex.org/I31419693"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076365895","display_name":"Adeyinka P. Adedigba","orcid":"https://orcid.org/0000-0001-8760-7881"},"institutions":[{"id":"https://openalex.org/I31419693","display_name":"Kyungpook National University","ror":"https://ror.org/040c17130","country_code":"KR","type":"education","lineage":["https://openalex.org/I31419693"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Adeyinka P. Adedigba","raw_affiliation_strings":["Kyungpook National University,Department of Artificial Intelligence,Daegu,South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kyungpook National University,Department of Artificial Intelligence,Daegu,South Korea","institution_ids":["https://openalex.org/I31419693"]}]},{"author_position":"last","author":{"id":null,"display_name":"Rammohan Mallipeddi","orcid":null},"institutions":[{"id":"https://openalex.org/I31419693","display_name":"Kyungpook National University","ror":"https://ror.org/040c17130","country_code":"KR","type":"education","lineage":["https://openalex.org/I31419693"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Rammohan Mallipeddi","raw_affiliation_strings":["Kyungpook National University,Department of Artificial Intelligence,Daegu,South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kyungpook National University,Department of Artificial Intelligence,Daegu,South Korea","institution_ids":["https://openalex.org/I31419693"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I31419693"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"547","last_page":"552"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9147999882698059,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9147999882698059,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T13918","display_name":"Advanced Data and IoT Technologies","score":0.003700000001117587,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10494","display_name":"Plant Virus Research Studies","score":0.0031999999191612005,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.603600025177002},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5253000259399414},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.48910000920295715},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.45579999685287476},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.43459999561309814},{"id":"https://openalex.org/keywords/plant-disease","display_name":"Plant disease","score":0.4221999943256378},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.3968000113964081},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.3725999891757965}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6948000192642212},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6079999804496765},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.603600025177002},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5253000259399414},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5120999813079834},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.48910000920295715},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.45579999685287476},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.43459999561309814},{"id":"https://openalex.org/C3019235130","wikidata":"https://www.wikidata.org/wiki/Q188956","display_name":"Plant disease","level":2,"score":0.4221999943256378},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.3968000113964081},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.3725999891757965},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36010000109672546},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.35269999504089355},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3337000012397766},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3280999958515167},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.2700999975204468},{"id":"https://openalex.org/C2779070825","wikidata":"https://www.wikidata.org/wiki/Q760434","display_name":"Augment","level":2,"score":0.26910001039505005},{"id":"https://openalex.org/C138958017","wikidata":"https://www.wikidata.org/wiki/Q190087","display_name":"Data type","level":2,"score":0.2574999928474426},{"id":"https://openalex.org/C2985179745","wikidata":"https://www.wikidata.org/wiki/Q131449","display_name":"Plant species","level":2,"score":0.2538999915122986},{"id":"https://openalex.org/C55037315","wikidata":"https://www.wikidata.org/wiki/Q5421151","display_name":"Experimental data","level":2,"score":0.2533999979496002}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ictc66702.2025.11388431","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ictc66702.2025.11388431","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 16th International Conference on Information and Communication Technology Convergence (ICTC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.41629350185394287,"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2473156356","https://openalex.org/W2789255992","https://openalex.org/W2962793481","https://openalex.org/W3001160332","https://openalex.org/W3091123787","https://openalex.org/W3111506096","https://openalex.org/W4303045583","https://openalex.org/W4317734434","https://openalex.org/W4360765180","https://openalex.org/W4389565929","https://openalex.org/W4392121229","https://openalex.org/W4400939651","https://openalex.org/W4402700275","https://openalex.org/W4409740852","https://openalex.org/W4411173787"],"related_works":[],"abstract_inverted_index":{"Deep":[0],"learning":[1,100],"models":[2,13,35,46,139],"have":[3,36],"been":[4,37],"developed":[5],"for":[6,39],"automated":[7],"plant":[8],"disease":[9,122,172],"classification.":[10],"However,":[11],"these":[12],"often":[14],"suffer":[15],"from":[16,56,88],"limited":[17],"data":[18,23,40,67,131,146,161],"diversity,":[19],"especially":[20],"when":[21,128],"training":[22],"does":[24],"not":[25],"reflect":[26],"real":[27],"environmental":[28],"conditions.":[29],"To":[30],"address":[31],"this":[32,108],"issue,":[33],"generative":[34,45,70],"proposed":[38,82],"augmentation.":[41],"Despite":[42],"their":[43],"potential,":[44],"face":[47],"challenges":[48],"such":[49],"as":[50],"mode":[51],"collapse,":[52],"which":[53],"prevents":[54],"them":[55],"guaranteeing":[57],"sufficient":[58],"diversity":[59],"in":[60,154,169],"the":[61,96,111,134,142,170],"generated":[62],"data.":[63],"As":[64],"a":[65,118,151],"result,":[66],"augmentation":[68],"using":[69],"adversarial":[71],"networks":[72],"(GANs)":[73],"can":[74],"sometimes":[75],"degrade":[76],"algorithm":[77],"performance.":[78,155],"Recently,":[79],"Leaf-GAN":[80],"was":[81],"to":[83,91,147,150],"generate":[84],"diseased":[85],"leaf":[86,121],"images":[87,116],"healthy":[89],"ones,":[90],"augment":[92],"datasets":[93],"and":[94],"improve":[95],"performance":[97,106],"of":[98,113,136,144],"deep":[99],"models.":[101],"While":[102],"prior":[103],"work":[104],"claimed":[105],"gains,":[107],"study":[109],"investigates":[110],"effect":[112],"Leaf-GAN\u2013generated":[114,160],"synthetic":[115,130,145],"on":[117],"real-world":[119],"tomato":[120,171],"dataset.":[123],"Our":[124],"results":[125],"show":[126],"that":[127,159,165],"10%":[129],"is":[132],"added,":[133],"accuracy":[135],"all":[137],"tested":[138],"decreases.":[140],"Increasing":[141],"proportion":[143],"25%":[148],"leads":[149],"continued":[152],"decline":[153],"These":[156],"findings":[157],"suggest":[158],"may":[162],"introduce":[163],"inconsistencies":[164],"hinder":[166],"model":[167],"generalization":[168],"classification":[173],"task.":[174]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-02-20T00:00:00"}