Federated learning (FL) is a technique that allows multiple participants to collaboratively
train a Deep Neural Network (DNN) without the need to centralize their data. Among other …

The current study presents a new methodology for zero watermarking that relies on the
discrete wavelet transform (DWT) and an improved MobileNetV2 convolutional neural …

The adoption of “artificial intelligence (AI) in drug discovery”, where AI is used in the process
of pharmaceutical research and development, is progressing. By using the ability to process …

Deep Neural Networks (DNNs), from AlexNet to ResNet to ChatGPT, have made
revolutionary progress in recent years, and are widely used in various fields. The high …

At present, watermarking techniques play an important role in protecting digital images. To
date, many classical watermarking schemes have been developed to protect images based …

The Internet of Things (IoT) is a network of millions of smart devices and sensors connected
to a network. These devices are used in smart cities, public transportation, smart grids and …

Imperceptibility, embedding capacity and robustness are basic requirements of an image
watermarking algorithm. There is always a trade-off among these requirements. To achieve …

Abstract Background Surgical site infections (SSIs) are a significant health care problem as
they can cause increased medical costs and increased morbidity and mortality. Assessing a …

Federated learning (FL) allows multiple participants to collaboratively build deep learning
(DL) models without directly sharing data. Consequently, the issue of copyright protection in …

The active use of the Internet and multimedia content has recently escalated copyright
violations. Digital content, especially images and videos are subject to vulnerable attacks. It …