Hany S. Khalifa

TL;DR: In this paper, an effective computer-aided diagnosis (CAD) system is presented to detect MI signals using the convolution neural network (CNN) for urban healthcare in smart cities.

TL;DR: An effective computer-aided diagnosis (CAD) system is presented to detect MI signals using the convolution neural network (CNN) for urban healthcare in smart cities and achieves a high accuracy surpasses the existing methods.

TL;DR: This work designs a QWs-based novel image steganography mechanism for cloud systems, which the embedding/extraction process for the secret object is based on quantum concepts and opens the door for quantum technologies to be combined with information hiding techniques to achieve better security.

TL;DR: In this article, the authors proposed an image cryptosystem for data transfer in cloud-based smart cities using the cascading of Logistic-Chebyshev and Logistic Sine maps.

TL;DR: The performed analysis provides the proposed approach a strong base in the field of image steganography and helps to select one channel from (RGB) of the cover image that will host the secret bits.