1 code implementation • journal 2021 • Sara Al-Emadi, Abdulla Al-Ali, Abdulaziz Al-Ali
In this paper, we aim to fill this gap by introducing a hybrid drone acoustic dataset composed of recorded drone audio clips and artificially generated drone audio samples using a state-of-the-art deep learning technique known as the Generative Adversarial Network.
no code implementations • 23 May 2021 • Mohammed Jouhari, Abdulla Al-Ali, Emna Baccour, Amr Mohamed, Aiman Erbad, Mohsen Guizani, Mounir Hamdi
Unmanned Aerial Vehicles (UAVs) have attracted great interest in the last few years owing to their ability to cover large areas and access difficult and hazardous target zones, which is not the case of traditional systems relying on direct observations obtained from fixed cameras and sensors.
no code implementations • 27 Jun 2020 • Alaa Awad Abdellatif, Lutfi Samara, Amr Mohamed, Mohsen Guizani, Aiman Erbad, Abdulla Al-Ali
Rapid evolution of wireless medical devices and network technologies has fostered the growth of remote monitoring systems.
no code implementations • 23 Oct 2018 • Reza Shakeri, Mohammed Ali Al-Garadi, Ahmed Badawy, Amr Mohamed, Tamer Khattab, Abdulla Al-Ali, Khaled A. Harras, Mohsen Guizani
We present and propose state-of-the-art algorithms to address design challenges with both quantitative and qualitative methods and map these challenges with important CPS applications to draw insightful conclusions on the challenges of each application.
no code implementations • 29 Jul 2018 • Mohammed Ali Al-Garadi, Amr Mohamed, Abdulla Al-Ali, Xiaojiang Du, Mohsen Guizani
Consequently, ML/DL methods are important in transforming the security of IoT systems from merely facilitating secure communication between devices to security-based intelligence systems.