Comprehensive Evaluation of Deepfake Detection Models: Accuracy, Generalization, and Resilience to Adversarial Attacks
The rise of deepfakes—synthetic media generated using artificial intelligence—threatens digital content authenticity, facilitating misinformation and manipulation. However, deepfakes can also depict real or entirely fictitious individuals, leveraging state-of-the-art techniques such as generative ad...
Saved in:
| Main Authors: | Maryam Abbasi, Paulo Váz, José Silva, Pedro Martins |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-01-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/3/1225 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Neural Network Ensemble Method for Deepfake Classification Using Golden Frame Selection
by: Khrystyna Lipianina-Honcharenko, et al.
Published: (2025-04-01) -
A Dual-Branch Fusion Model for Deepfake Detection Using Video Frames and Microexpression Features
by: Georgios Petmezas, et al.
Published: (2025-07-01) -
Ensemble-based sesame disease detection and classification using deep convolutional neural networks (CNN)
by: Abenet Alazar Hailu, et al.
Published: (2025-08-01) -
Deep learning-based detection and classification of acute lymphoblastic leukemia with explainable AI techniques
by: Debendra Muduli, et al.
Published: (2025-07-01) -
Design and development of an efficient RLNet prediction model for deepfake video detection
by: Varad Bhandarkawthekar, et al.
Published: (2025-07-01)