{"id":"https://openalex.org/W4379620320","doi":"https://doi.org/10.1145/3555776.3577769","title":"Robust DeepFake Detection Method based on Ensemble of ViT and CNN","display_name":"Robust DeepFake Detection Method based on Ensemble of ViT and CNN","publication_year":2023,"publication_date":"2023-03-27","ids":{"openalex":"https://openalex.org/W4379620320","doi":"https://doi.org/10.1145/3555776.3577769"},"language":"en","primary_location":{"id":"doi:10.1145/3555776.3577769","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3555776.3577769","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing","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/A5083085911","display_name":"H Nguyen Ha","orcid":"https://orcid.org/0000-0003-0687-9530"},"institutions":[{"id":"https://openalex.org/I141371507","display_name":"Soongsil University","ror":"https://ror.org/017xnm587","country_code":"KR","type":"education","lineage":["https://openalex.org/I141371507"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyunsoo Ha","raw_affiliation_strings":["Soongsil University, Seoul, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0003-0687-9530","affiliations":[{"raw_affiliation_string":"Soongsil University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I141371507"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041964327","display_name":"Minsang Kim","orcid":"https://orcid.org/0000-0002-7949-0764"},"institutions":[{"id":"https://openalex.org/I141371507","display_name":"Soongsil University","ror":"https://ror.org/017xnm587","country_code":"KR","type":"education","lineage":["https://openalex.org/I141371507"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Minsang Kim","raw_affiliation_strings":["Soongsil University, Seoul, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0002-7949-0764","affiliations":[{"raw_affiliation_string":"Soongsil University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I141371507"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103182794","display_name":"Songhun Han","orcid":"https://orcid.org/0000-0003-4003-1808"},"institutions":[{"id":"https://openalex.org/I141371507","display_name":"Soongsil University","ror":"https://ror.org/017xnm587","country_code":"KR","type":"education","lineage":["https://openalex.org/I141371507"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Songhun Han","raw_affiliation_strings":["Soongsil University, Seoul, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0003-4003-1808","affiliations":[{"raw_affiliation_string":"Soongsil University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I141371507"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048091080","display_name":"Sangjun Lee","orcid":"https://orcid.org/0000-0002-4251-7177"},"institutions":[{"id":"https://openalex.org/I141371507","display_name":"Soongsil University","ror":"https://ror.org/017xnm587","country_code":"KR","type":"education","lineage":["https://openalex.org/I141371507"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sangjun Lee","raw_affiliation_strings":["Soongsil University, Seoul, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0002-4251-7177","affiliations":[{"raw_affiliation_string":"Soongsil University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I141371507"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6725,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.70569381,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1092","last_page":"1095"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9991000294685364,"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/T11448","display_name":"Face recognition and analysis","score":0.9973000288009644,"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/computer-science","display_name":"Computer science","score":0.8643128871917725},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7043589353561401},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6945847868919373},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5484987497329712},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5359920263290405},{"id":"https://openalex.org/keywords/generative-adversarial-network","display_name":"Generative adversarial network","score":0.49216192960739136},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4915789067745209},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4584150016307831},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4495318830013275}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8643128871917725},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7043589353561401},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6945847868919373},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5484987497329712},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5359920263290405},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.49216192960739136},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4915789067745209},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4584150016307831},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4495318830013275},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3555776.3577769","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3555776.3577769","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4300000071525574,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G4993214011","display_name":null,"funder_award_id":"NRF-2021R1F1A1053194","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2124868070","https://openalex.org/W2165698076","https://openalex.org/W2341528187","https://openalex.org/W2559655401","https://openalex.org/W2936503027","https://openalex.org/W2954996726","https://openalex.org/W2989851933","https://openalex.org/W3019200173","https://openalex.org/W3038930935","https://openalex.org/W3101998545","https://openalex.org/W3125803510","https://openalex.org/W4251081792"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3029198973","https://openalex.org/W4385572368","https://openalex.org/W2888032422","https://openalex.org/W2996316059","https://openalex.org/W3178813832"],"abstract_inverted_index":{"With":[0],"the":[1,69],"development":[2],"of":[3,71,99],"convolutional":[4],"neural":[5],"networks":[6,11],"(CNN)":[7],"and":[8,61],"generative":[9],"adversarial":[10],"(GAN)":[12],"in":[13,91],"recent":[14],"years,":[15],"classifying":[16],"fake":[17],"videos":[18,93],"produced":[19],"through":[20,40,77],"DeepFake":[21,32,38,42,100],"has":[22,46,68],"become":[23],"a":[24,96],"very":[25],"difficult":[26],"task.":[27],"Most":[28],"previous":[29],"studies":[30],"on":[31,36],"Detection":[33],"were":[34],"focused":[35],"finding":[37],"artifacts":[39],"CNN.":[41],"detection":[43],"using":[44],"CNN":[45],"high":[47],"accuracy,":[48],"but":[49],"is":[50],"vulnerable":[51],"to":[52,74,82,85],"noisy":[53],"inputs":[54],"such":[55],"as":[56],"side":[57],"faces,":[58,60],"shadowed":[59],"low-quality":[62],"images.":[63],"In":[64],"addition,":[65],"although":[66],"it":[67,80],"advantage":[70],"being":[72],"able":[73],"learn":[75],"quickly":[76],"inductive":[78],"bias,":[79],"tends":[81],"be":[83],"overfitted":[84],"specific":[86],"datasets,":[87],"showing":[88],"low":[89],"accuracy":[90],"manipulated":[92],"created":[94],"with":[95],"different":[97],"type":[98],"from":[101],"training":[102],"datasets.":[103]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2}],"updated_date":"2026-06-13T07:54:00.901334","created_date":"2025-10-10T00:00:00"}
