Deepfakes are realistic-looking fake media generated by deep-learning algorithms that
iterate through large datasets until they have learned how to solve the given problem (ie …

In recent years, the proliferation of deep learning (DL) techniques has given rise to a
significant challenge in the form of deepfake videos, posing a grave threat to the authenticity …

Rapid advancements in deep learning-based technologies have developed several
synthetic video and audio generation methods producing incredibly hyper-realistic …

Due to the fast spread of data through digital media, individuals and societies must assess
the reliability of information. Deepfakes are not a novel idea but they are now a widespread …

Rapid advances in deep learning models have made it easier for public and crackers to
generate hyper-realistic deepfake videos in which faces are swapped. Such deepfake …

With the rising concern on model interpretability, the application of eXplainable AI (XAI) tools
on deepfake detection models has been a topic of interest recently. In image classification …

Cut-Test technique employs visual inspection of interior coloration, compartmentalization,
and defects of beans for effective classification of cocoa beans. However, due to its …

Face manipulation detection has become a recent research hotpot, and many detection
methods have been proposed. Most existing detection methods treat face manipulation …

Advanced driver assistance systems (ADASs), particularly pedestrian protection systems
(PPSs), have emerged as a hot research topic with the goal of enhancing traffic safety. The …

Recently, deepfake technology has become a popularly used technique for swapping faces
in images or videos that create forged data to mislead society. Detecting the originality of the …