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dc.contributor.authorNaskar, Gourab
dc.contributor.authorMohiuddin, Sk
dc.contributor.authorMalakar, Samir
dc.contributor.authorCuevas, Erik
dc.contributor.authorSarkar, Ram
dc.date.accessioned2024-09-19T08:15:06Z
dc.date.available2024-09-19T08:15:06Z
dc.date.issued2024-02-15
dc.description.abstractDeepfake is a type of face manipulation technique using deep learning that allows for the replacement of faces in videos in a very realistic way. While this technology has many practical uses, if used maliciously, it can have a significant number of bad impacts on society, such as spreading fake news or cyberbullying. Therefore, the ability to detect deepfake has become a pressing need. This paper aims to address the problem of deepfake detection by identifying deepfake forgeries in video sequences. In this paper, a solution to the said problem is presented, which at first uses a stacking based ensemble approach, where features obtained from two popular deep learning models, namely Xception and EfficientNet-B7, are combined. Then by selecting a near-optimal subset of features using a ranking based approach, the final classification is performed to classify real and fake videos using a meta-learner, called multi-layer perceptron. In our experimentation, we have achieved an accuracy of 96.33% on Celeb-DF (V2) dataset and 98.00% on the FaceForensics++ dataset using the meta-learning model both of which are higher than the individual base models. Various types of experiments have been conducted to validate the robustness of the current method.en_US
dc.identifier.citationNaskar, Mohiuddin, Malakar, Cuevas, Sarkar. Deepfake detection using deep feature stacking and meta-learning. Heliyon. 2024;10(4)en_US
dc.identifier.cristinIDFRIDAID 2254819
dc.identifier.doi10.1016/j.heliyon.2024.e25933
dc.identifier.issn2405-8440
dc.identifier.urihttps://hdl.handle.net/10037/34788
dc.language.isoengen_US
dc.publisherElsevier
dc.relation.journalHeliyon
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2024 The Author(s)en_US
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0en_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)en_US
dc.titleDeepfake detection using deep feature stacking and meta-learningen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)