{"id":"https://openalex.org/W4403278195","doi":"https://doi.org/10.1109/tce.2024.3476477","title":"Efficient Deepfake Detection via Layer-Frozen Assisted Dual Attention Network for Consumer Imaging Devices","display_name":"Efficient Deepfake Detection via Layer-Frozen Assisted Dual Attention Network for Consumer Imaging Devices","publication_year":2024,"publication_date":"2024-10-09","ids":{"openalex":"https://openalex.org/W4403278195","doi":"https://doi.org/10.1109/tce.2024.3476477"},"language":"en","primary_location":{"id":"doi:10.1109/tce.2024.3476477","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tce.2024.3476477","pdf_url":null,"source":{"id":"https://openalex.org/S126824455","display_name":"IEEE Transactions on Consumer Electronics","issn_l":"0098-3063","issn":["0098-3063","1558-4127"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Consumer Electronics","raw_type":"journal-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/A5100561952","display_name":"Muhammad Talha Usman","orcid":"https://orcid.org/0009-0001-9934-7818"},"institutions":[{"id":"https://openalex.org/I12832649","display_name":"Gachon University","ror":"https://ror.org/03ryywt80","country_code":"KR","type":"education","lineage":["https://openalex.org/I12832649"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Muhammad Talha Usman","raw_affiliation_strings":["School of Computing, Gachon University, Seongnam, South Korea"],"raw_orcid":"https://orcid.org/0009-0001-9934-7818","affiliations":[{"raw_affiliation_string":"School of Computing, Gachon University, Seongnam, South Korea","institution_ids":["https://openalex.org/I12832649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101859619","display_name":"Habib Khan","orcid":"https://orcid.org/0000-0003-2722-7574"},"institutions":[{"id":"https://openalex.org/I12832649","display_name":"Gachon University","ror":"https://ror.org/03ryywt80","country_code":"KR","type":"education","lineage":["https://openalex.org/I12832649"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Habib Khan","raw_affiliation_strings":["School of Computing, Gachon University, Seongnam, South Korea"],"raw_orcid":"https://orcid.org/0000-0003-2722-7574","affiliations":[{"raw_affiliation_string":"School of Computing, Gachon University, Seongnam, South Korea","institution_ids":["https://openalex.org/I12832649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101789947","display_name":"Sushil Kumar Singh","orcid":"https://orcid.org/0000-0003-1418-3218"},"institutions":[{"id":"https://openalex.org/I3132999081","display_name":"Marwadi University","ror":"https://ror.org/030dn1812","country_code":"IN","type":"education","lineage":["https://openalex.org/I3132999081"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sushil Kumar Singh","raw_affiliation_strings":["Department of Computer Engineering, Marwadi University, Rajkot, India","Department of Computer Engineering Marwadi University, Rajkot, Gujarat, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Marwadi University, Rajkot, India","institution_ids":["https://openalex.org/I3132999081"]},{"raw_affiliation_string":"Department of Computer Engineering Marwadi University, Rajkot, Gujarat, India","institution_ids":["https://openalex.org/I3132999081"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100690117","display_name":"Mi Young Lee","orcid":"https://orcid.org/0000-0002-8139-7091"},"institutions":[{"id":"https://openalex.org/I67900169","display_name":"Chung-Ang University","ror":"https://ror.org/01r024a98","country_code":"KR","type":"education","lineage":["https://openalex.org/I67900169"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Mi Young Lee","raw_affiliation_strings":["School of Computing, Chung-Ang University, Seoul, South Korea","Chung-Ang University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-8139-7091","affiliations":[{"raw_affiliation_string":"School of Computing, Chung-Ang University, Seoul, South Korea","institution_ids":["https://openalex.org/I67900169"]},{"raw_affiliation_string":"Chung-Ang University, Seoul, South Korea","institution_ids":["https://openalex.org/I67900169"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047917337","display_name":"Jakeoung Koo","orcid":"https://orcid.org/0000-0003-2614-3424"},"institutions":[{"id":"https://openalex.org/I12832649","display_name":"Gachon University","ror":"https://ror.org/03ryywt80","country_code":"KR","type":"education","lineage":["https://openalex.org/I12832649"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"JaKeoung Koo","raw_affiliation_strings":["School of Computing, Gachon University, Seongnam, South Korea"],"raw_orcid":"https://orcid.org/0000-0003-2614-3424","affiliations":[{"raw_affiliation_string":"School of Computing, Gachon University, Seongnam, South Korea","institution_ids":["https://openalex.org/I12832649"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100561952"],"corresponding_institution_ids":["https://openalex.org/I12832649"],"apc_list":null,"apc_paid":null,"fwci":17.6523,"has_fulltext":false,"cited_by_count":53,"citation_normalized_percentile":{"value":0.99488107,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"71","issue":"1","first_page":"281","last_page":"291"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9883000254631042,"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"}},"topics":[{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9883000254631042,"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"}},{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9771999716758728,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9746000170707703,"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/dual-layer","display_name":"Dual layer","score":0.6300082206726074},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.5994991064071655},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.5601805448532104},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5304744839668274},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.36029142141342163},{"id":"https://openalex.org/keywords/nanotechnology","display_name":"Nanotechnology","score":0.20884090662002563}],"concepts":[{"id":"https://openalex.org/C2993148961","wikidata":"https://www.wikidata.org/wiki/Q5294","display_name":"Dual layer","level":3,"score":0.6300082206726074},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.5994991064071655},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.5601805448532104},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5304744839668274},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.36029142141342163},{"id":"https://openalex.org/C171250308","wikidata":"https://www.wikidata.org/wiki/Q11468","display_name":"Nanotechnology","level":1,"score":0.20884090662002563},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tce.2024.3476477","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tce.2024.3476477","pdf_url":null,"source":{"id":"https://openalex.org/S126824455","display_name":"IEEE Transactions on Consumer Electronics","issn_l":"0098-3063","issn":["0098-3063","1558-4127"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Consumer Electronics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4981246048","display_name":null,"funder_award_id":"No. RS-2023-00240740","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":53,"referenced_works":["https://openalex.org/W2076587863","https://openalex.org/W2531409750","https://openalex.org/W2791208937","https://openalex.org/W2891145043","https://openalex.org/W2909336075","https://openalex.org/W2911424785","https://openalex.org/W2963043696","https://openalex.org/W2982058372","https://openalex.org/W2998449272","https://openalex.org/W3012437309","https://openalex.org/W3034196597","https://openalex.org/W3034713808","https://openalex.org/W3036576316","https://openalex.org/W3037967553","https://openalex.org/W3093010840","https://openalex.org/W3116036704","https://openalex.org/W3158353280","https://openalex.org/W3158766194","https://openalex.org/W3169588269","https://openalex.org/W3173317327","https://openalex.org/W3174508664","https://openalex.org/W3174572554","https://openalex.org/W3174656926","https://openalex.org/W3175342695","https://openalex.org/W3179079440","https://openalex.org/W3196204467","https://openalex.org/W4200635057","https://openalex.org/W4210426155","https://openalex.org/W4288102863","https://openalex.org/W4289752563","https://openalex.org/W4312610635","https://openalex.org/W4312967678","https://openalex.org/W4317616184","https://openalex.org/W4363675626","https://openalex.org/W4364305500","https://openalex.org/W4372260356","https://openalex.org/W4378448087","https://openalex.org/W4385805162","https://openalex.org/W4386744346","https://openalex.org/W4389104848","https://openalex.org/W4389240355","https://openalex.org/W4389265494","https://openalex.org/W4390691233","https://openalex.org/W4390691716","https://openalex.org/W4394806392","https://openalex.org/W4401051167","https://openalex.org/W6756046522","https://openalex.org/W6762718338","https://openalex.org/W6764542186","https://openalex.org/W6784810453","https://openalex.org/W6790220185","https://openalex.org/W6792139253","https://openalex.org/W6810065566"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W4246450666","https://openalex.org/W4388998267","https://openalex.org/W2898370298","https://openalex.org/W2066174985","https://openalex.org/W2329901306","https://openalex.org/W3026417777","https://openalex.org/W2221506820","https://openalex.org/W1971013904"],"abstract_inverted_index":{"The":[0,133],"advancement":[1],"of":[2,13,139,158,163,196],"open-source":[3],"frameworks":[4],"and":[5,92,130,181,219,233],"user-friendly":[6],"manipulation":[7],"applications":[8],"has":[9],"accelerated":[10],"the":[11,44,54,80,118,140,155,169,193,215],"spread":[12],"deep":[14],"fakes.":[15],"In":[16],"this":[17,33,71],"study,":[18],"we":[19,153,206],"proposed":[20],"optimal":[21],"features":[22,134,165],"assisted":[23,136],"with":[24,74,142],"a":[25,75,174,222,237],"dual":[26],"attention":[27,90,94],"(DA)":[28],"network":[29,119,141,225],"strategy":[30],"to":[31,62,97,107,120,145,166,185,230],"combat":[32],"proliferation":[34],"in":[35,137,199,245],"consumer":[36,200,246],"imaging":[37,247],"devices.":[38],"We":[39,69,172],"employed":[40,173],"EfficientNetV2":[41],"(ENV2)":[42],"as":[43],"primary":[45],"feature":[46,66,99,105,114,126],"extractor,":[47],"initially":[48],"utilizing":[49],"its":[50,59],"pre-trained":[51],"weights":[52],"from":[53],"ImageNet":[55],"dataset":[56],"while":[57],"keeping":[58],"layers":[60,157,180],"frozen":[61],"leverage":[63],"their":[64],"rich":[65],"extraction":[67],"capabilities.":[68],"enhance":[70],"base":[72],"model":[73],"DA":[76],"module":[77],"that":[78],"integrates":[79],"Convolutional":[81],"Block":[82],"Attention":[83],"Module":[84],"(CBAM),":[85],"which":[86],"utilizes":[87],"both":[88],"channel":[89],"(CA)":[91],"spatial":[93],"(SA)":[95],"mechanisms":[96],"improve":[98],"representation.":[100],"CA":[101],"dynamically":[102],"adjusts":[103],"channel-wise":[104],"responses":[106],"capture":[108],"interdependencies":[109],"between":[110],"channels,":[111],"thereby":[112],"improving":[113],"discrimination.":[115],"SA":[116],"allows":[117],"focus":[121,146],"on":[122,147,210],"important":[123],"regions":[124],"within":[125],"maps,":[127],"enhancing":[128],"localization":[129],"reducing":[131],"noise.":[132],"are":[135],"multi-stages":[138],"residual":[143],"fashion":[144],"discriminative":[148],"visual":[149],"information.":[150],"During":[151],"fine-tuning,":[152],"unfreeze":[154],"deeper":[156],"ENV2":[159],"for":[160,240],"further":[161],"refinement":[162],"learned":[164],"better":[167],"suit":[168],"deepfake":[170,242],"dataset.":[171],"targeted":[175],"fine-tuning":[176],"approach,":[177],"unfreezing":[178],"specific":[179],"applying":[182],"iterative":[183],"adjustments":[184],"optimize":[186],"performance,":[187],"providing":[188],"valuable":[189],"insights":[190],"into":[191],"countering":[192],"growing":[194],"use":[195],"synthetic":[197],"media":[198],"imaging.":[201],"To":[202],"validate":[203],"our":[204,224],"network,":[205],"conducted":[207],"comprehensive":[208],"experiments":[209],"four":[211],"benchmark":[212],"datasets:":[213],"FaceForensics++,":[214],"World":[216],"Leaders,":[217],"Celeb-DF,":[218],"DFDC.":[220],"As":[221],"result,":[223],"achieved":[226],"superior":[227],"performance":[228],"compared":[229],"existing":[231],"benchmarks":[232],"state-of-the-art":[234],"approaches,":[235],"offering":[236],"promising":[238],"solution":[239],"robust":[241],"detection":[243],"(DD)":[244],"technologies.":[248]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":42},{"year":2024,"cited_by_count":5}],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}
