Internet of Things (IoT)
LEO Satellite Communications
Energy-Efficient Power Allocation
Green Wireless Sensor Networks
Applied data Analytics, Machine/Deep Learning, optimization
Cognitive, Low SNR, MIMO communications.
Mohamed Karaa, Raed Bahria, Hakim Ghazzai, and Lokman Sboui
We develop a semantic compression framework for low-bandwidth video surveillance, extracting abstract representations using state-of-the-art object detection, tracking and captioning models.
Nourhane Sboui, Raed Bahria, Hakim Ghazzai, Sameh Najeh and Lokman Sboui
We introduce a comprehensive no-reference deep image quality assessment (NR-DIQA) framework designed to effectively manage LEO satellite images for Earth observation (EO) by identifying and filtering distorted and anomalous images before transmission.
Mohamed Karaa, Hakim Ghazzai, and Lokman Sboui
We present an image dataset of snow-covered urban roads captured by traffic cameras during the season. We discuss the dataset acquisition methodology, as well a benchmark problem for automating its annotation with snow levels, and its potential applications.
Mohamed Karaa, Hakim Ghazzai, and Lokman Sboui
An AI-based annotation system for a dataset of snow-covered road images into four snow level categories. The annotation enables the training of supervised classification models.
Sundos Mojahed, Rejean Drouin, Lokman Sboui
ODACE is a novel platform that automates the manual mobile phone certification process using Appium and ADP to verify mobile phone functions, significantly reducing the time and effort required for certification.
Saad Abobakr, Mahmud Alosta, Mohamed Amine Abdelkefi, Amine El Kaouachi, Lokman Sboui
ODACE is a novel platform that automates the manual mobile phone certification process using Appium and ADP to verify mobile phone functions, significantly reducing the time and effort required for certification.
Allafi Omran, Mohamed Cheriet, Lokman Sboui
A novel scheme to enhance network resilience and efficiency in post-disaster and crowded cellular networks by integrating unmanned aerial vehicles (UAVs) and satellites.
Lokman Sboui, Hakim Ghazzai, Zouheir Rezki, Mohamed-Slim Alouini
A study of the achievable rate of a 5G scenario where a UAV relay is extending the wireless network and is serving both primary and secondary users in a cognitive radio framework.
Advisor: Prof. Mohamed-Slim Alouini, King Abdullah University of Science and Technology (KAUST)
My doctoral research addressed the exponential increase in global data traffic through the development of 5G frameworks and cognitive radio (CR) concepts. The study aimed to mitigate spectrum scarcity while enhancing performance in terms of reliability, scalability, and energy efficiency.