EfficientNet with transformer integrations for enhancing deepfake detections

The emergence of Artificial Intelligence has brought about significant advancements, yet it also raises concerns, notably regarding the proliferation of "deepfakes" – digitally altered facial media that blurs the line between reality and fabrication. Extensive research has been conducted t...

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Bibliographic Details
Main Author: Varsha, Saravanabavan
Other Authors: Deepu Rajan
Format: Final Year Project (FYP)
Language:English
Published: Nanyang Technological University 2024
Subjects:
Online Access:https://hdl.handle.net/10356/175419
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author Varsha, Saravanabavan
author2 Deepu Rajan
author_facet Deepu Rajan
Varsha, Saravanabavan
author_sort Varsha, Saravanabavan
collection NTU
description The emergence of Artificial Intelligence has brought about significant advancements, yet it also raises concerns, notably regarding the proliferation of "deepfakes" – digitally altered facial media that blurs the line between reality and fabrication. Extensive research has been conducted to develop methods for detecting deepfakes, aiming to mitigate their adverse impacts. This study investigates popular deepfake generation and detection techniques, assessing their effectiveness and limitations. Building upon this, the architectures and performances of EfficientNetB4 were explored and integrated with Spatial and Vision Transformer to create two resource-efficient and accurate deepfake detection models trained on the FaceForensics++ dataset. Evaluation metrics such as accuracy, F1 score, and Area Under Curve (AUC) were employed to compare the proposed architectures with existing models. The proposed EfficientNetB4 models integrated with Spatial Transformer and Vision Transformer have achieved accuracies of 87.50% and 91.43% respectively.
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spelling ntu-10356/1754192024-05-10T15:39:52Z EfficientNet with transformer integrations for enhancing deepfake detections Varsha, Saravanabavan Deepu Rajan School of Computer Science and Engineering ASDRajan@ntu.edu.sg Computer and Information Science Deepfakes Efficientnet Transformer The emergence of Artificial Intelligence has brought about significant advancements, yet it also raises concerns, notably regarding the proliferation of "deepfakes" – digitally altered facial media that blurs the line between reality and fabrication. Extensive research has been conducted to develop methods for detecting deepfakes, aiming to mitigate their adverse impacts. This study investigates popular deepfake generation and detection techniques, assessing their effectiveness and limitations. Building upon this, the architectures and performances of EfficientNetB4 were explored and integrated with Spatial and Vision Transformer to create two resource-efficient and accurate deepfake detection models trained on the FaceForensics++ dataset. Evaluation metrics such as accuracy, F1 score, and Area Under Curve (AUC) were employed to compare the proposed architectures with existing models. The proposed EfficientNetB4 models integrated with Spatial Transformer and Vision Transformer have achieved accuracies of 87.50% and 91.43% respectively. Bachelor's degree 2024-04-24T02:06:47Z 2024-04-24T02:06:47Z 2024 Final Year Project (FYP) Varsha, S. (2024). EfficientNet with transformer integrations for enhancing deepfake detections. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/175419 https://hdl.handle.net/10356/175419 en SCSE23-0535 application/pdf Nanyang Technological University
spellingShingle Computer and Information Science
Deepfakes
Efficientnet
Transformer
Varsha, Saravanabavan
EfficientNet with transformer integrations for enhancing deepfake detections
title EfficientNet with transformer integrations for enhancing deepfake detections
title_full EfficientNet with transformer integrations for enhancing deepfake detections
title_fullStr EfficientNet with transformer integrations for enhancing deepfake detections
title_full_unstemmed EfficientNet with transformer integrations for enhancing deepfake detections
title_short EfficientNet with transformer integrations for enhancing deepfake detections
title_sort efficientnet with transformer integrations for enhancing deepfake detections
topic Computer and Information Science
Deepfakes
Efficientnet
Transformer
url https://hdl.handle.net/10356/175419
work_keys_str_mv AT varshasaravanabavan efficientnetwithtransformerintegrationsforenhancingdeepfakedetections