Images are promising information carriers when compared to other media documents in the
healthcare domain. However, digital data transmission over unprotected wired or wireless …

Deep learning models, such as convolutional neural network (CNN), are popular now a day
to solve various complex problems in medical and other fields, such as image classification …

Diabetic retinopathy (DR), a long-term complication of diabetes, is notoriously hard to detect
in its early stages due to the fact that it only shows a subset of symptoms. Standard …

Artificial Intelligence (AI) techniques have advanced to generate face images of nonexistent
yet photorealistic persons. Despite positive applications, AI-synthesized faces have been …

With the development of diffusion-based customization methods like DreamBooth,
individuals now have access to train the models that can generate their personalized …

Deepfake technology presents significant challenges for digital media forensics. As
deepfakes become increasingly sophisticated, the ability to detect and attribute manipulated …

Hyper-realistic avatars in the metaverse have already raised security concerns about
deepfake techniques, deepfakes involving generated video “recording” may be mistaken for …

Deepfake detection has become an essential task in combating the proliferation of
manipulated media. Current methods of deepfake detection typically use a Sequential …

Human perception possesses the remarkable ability to mentally reconstruct the complete
structure of occluded objects, which has inspired researchers to pursue amodal instance …

We present a novel approach to detect fake news in Internet of Things (IoT) applications. By
investigating federated learning and trusted authority methods, we address the issue of data …