Researchers have introduced a robust feature similarity learning framework that achieves high deepfake detection accuracy and withstands adversarial perturbations.
A systematic review of 101 studies published between 2021 and 2025 finds that AI-based deepfake detectors often exceed 95% accuracy ...
A PRISMA-based systematic review of 142 primary studies categorises AI deepfake generation and detection methods and identifies dataset bias, poor ...
A physics-inspired deepfake detector that fuses luminance-gradient descriptors with RGB channels achieved up to 99.669 percent held-out accuracy on facial-image ...
Researchers propose an SGDFD framework that decomposes AI-generated content detection into semantic and forgery subspaces and splits the single fake ...
Researchers have developed FedHybrid-ViT, a privacy-preserving framework that fuses convolutional and transformer models within federated learning to detect deepfakes across ...
A new systematic review finds that hybrid deep learning and metaheuristic optimization frameworks achieve 98 to 100 percent accuracy in ...
In the rapidly evolving field of artificial intelligence, one of the most critical challenges facing researchers today is the detection ...
