{"id":"https://openalex.org/W7138907475","doi":"https://doi.org/10.1109/kst67832.2026.11432380","title":"M-GenCheck2: Fast Detection and Source Attribution of AI-Generated Images Using Deep Learning","display_name":"M-GenCheck2: Fast Detection and Source Attribution of AI-Generated Images Using Deep Learning","publication_year":2026,"publication_date":"2026-01-21","ids":{"openalex":"https://openalex.org/W7138907475","doi":"https://doi.org/10.1109/kst67832.2026.11432380"},"language":null,"primary_location":{"id":"doi:10.1109/kst67832.2026.11432380","is_oa":false,"landing_page_url":"https://doi.org/10.1109/kst67832.2026.11432380","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 18th International Conference on Knowledge and Smart Technology (KST)","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/A5069004363","display_name":"Nontawat Thongsibsong","orcid":null},"institutions":[{"id":"https://openalex.org/I34002243","display_name":"Mae Fah Luang University","ror":"https://ror.org/00mwhaw71","country_code":"TH","type":"education","lineage":["https://openalex.org/I34002243"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Nontawat Thongsibsong","raw_affiliation_strings":["Mae Fah Luang University,Center of Excellence in AI and Emerging Technologies, School of Applied Digital Technology,Chiang Rai,Thailand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mae Fah Luang University,Center of Excellence in AI and Emerging Technologies, School of Applied Digital Technology,Chiang Rai,Thailand","institution_ids":["https://openalex.org/I34002243"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083187666","display_name":"Surapol Vorapatratorn","orcid":"https://orcid.org/0000-0001-5705-8236"},"institutions":[{"id":"https://openalex.org/I34002243","display_name":"Mae Fah Luang University","ror":"https://ror.org/00mwhaw71","country_code":"TH","type":"education","lineage":["https://openalex.org/I34002243"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Surapol Vorapatratorn","raw_affiliation_strings":["Mae Fah Luang University,Center of Excellence in AI and Emerging Technologies, School of Applied Digital Technology,Chiang Rai,Thailand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mae Fah Luang University,Center of Excellence in AI and Emerging Technologies, School of Applied Digital Technology,Chiang Rai,Thailand","institution_ids":["https://openalex.org/I34002243"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I34002243"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.28860446,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"367","last_page":"371"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.3871999979019165,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.3871999979019165,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.1315000057220459,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.048900000751018524,"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/usable","display_name":"USable","score":0.6398000121116638},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6161999702453613},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5634999871253967},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5325999855995178},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.522599995136261},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.5213000178337097},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.45899999141693115},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.4390000104904175},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3831999897956848}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7789000272750854},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7634999752044678},{"id":"https://openalex.org/C2780615836","wikidata":"https://www.wikidata.org/wiki/Q2471869","display_name":"USable","level":2,"score":0.6398000121116638},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6161999702453613},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5634999871253967},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5325999855995178},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.522599995136261},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.5213000178337097},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.45899999141693115},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.4390000104904175},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41110000014305115},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3831999897956848},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37929999828338623},{"id":"https://openalex.org/C143299363","wikidata":"https://www.wikidata.org/wiki/Q900584","display_name":"Attribution","level":2,"score":0.3723999857902527},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.35910001397132874},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.35589998960494995},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3546000123023987},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.34549999237060547},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.34439998865127563},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2662000060081482},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.26190000772476196},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.2556999921798706},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.25529998540878296},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.2531000077724457},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.2524000108242035}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/kst67832.2026.11432380","is_oa":false,"landing_page_url":"https://doi.org/10.1109/kst67832.2026.11432380","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 18th International Conference on Knowledge and Smart Technology (KST)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.6163537502288818}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Generative":[0],"artificial":[1],"intelligence":[2],"makes":[3],"it":[4,11],"easy":[5],"to":[6],"create":[7],"photorealistic":[8],"images,":[9],"but":[10],"also":[12],"raises":[13],"concerns":[14],"about":[15],"trust,":[16],"misinformation,":[17],"and":[18,41,62,67,83,100,114,128,156,167,196],"academic":[19],"integrity.":[20],"This":[21],"paper":[22],"presents":[23],"M-GenCheck2,":[24],"a":[25,45,162,188],"convolutional":[26],"neural":[27],"network-based":[28],"system":[29,184],"for":[30,105],"fast":[31],"source":[32],"attribution":[33,108,122],"of":[34,47,77,89,178],"AI-generated":[35,49],"images.":[36],"The":[37,183],"model":[38],"uses":[39],"EfficientNet-B0":[40],"is":[42,185],"trained":[43],"on":[44,79,91],"dataset":[46],"3,205":[48],"images":[50],"collected":[51],"from":[52],"four":[53],"major":[54],"image":[55,201],"generators,":[56],"namely":[57],"MidJourney,":[58],"Stable":[59],"Diffusion,":[60],"DALL\u2022E,":[61],"Flux,":[63],"covering":[64],"diverse":[65],"prompts":[66],"visual":[68],"styles.":[69],"MGenCheck2":[70],"achieves":[71],"91.89%":[72],"accuracy":[73,85,166,171],"with":[74,86,96,125,172],"an":[75,87,92,173],"F1-score":[76,88],"0.9189":[78],"the":[80],"training":[81,113],"set":[82],"66.86%":[84],"0.6024":[90],"unseen":[93,115],"test":[94],"set,":[95],"relatively":[97],"balanced":[98],"precision":[99],"recall,":[101],"indicating":[102],"reasonable":[103],"generalization":[104],"multi-class":[106],"generator":[107],"under":[109],"distribution":[110],"shifts":[111],"between":[112,165],"data.":[116],"A":[117],"resolution":[118],"study":[119],"shows":[120,158],"that":[121,159,192],"performance":[123],"improves":[124],"input":[126],"quality":[127],"largely":[129],"stabilizes":[130],"at":[131,138],"around$\\mathbf{7":[132],"2":[133,144],"0}$pixels,":[134],"while":[135],"remaining":[136],"usable":[137],"very":[139],"low":[140],"resolutions":[141],"down":[142],"to$\\mathbf{1":[143],"0}$pixels.":[145],"Benchmarking":[146],"against":[147],"three":[148],"popular":[149],"online":[150],"AI-image":[151],"analysis":[152],"services,":[153],"Decopy.ai,":[154],"Wasitai.com,":[155],"Isgen.ai,":[157],"M-GenCheck2":[160],"provides":[161,193],"practical":[163],"trade-off":[164],"latency,":[168],"achieving":[169],"72.0%":[170],"average":[174],"end-to-end":[175],"response":[176],"time":[177],"4.36":[179],"seconds":[180],"per":[181],"image.":[182],"deployed":[186],"as":[187],"lightweight":[189],"web":[190],"application":[191],"real-time":[194],"predictions":[195],"confidence":[197],"scores,":[198],"allowing":[199],"unrestricted":[200],"submission":[202],"without":[203],"registration.":[204]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-03-20T00:00:00"}