1 citations · 1 across the 4 of their papers we have counts for
4 papers
Deep Multimodal Learning for Real-Time DDoS Attacks Detection in Internet of Vehicles
Mohamed Ababsa, Soheyb Ribouh, Abdelhamid Malki +1
The progress and integration of intelligent transport systems (ITS) have therefore been central to creating safer and more efficient transport networks. The Internet of Vehicles (I…
Deep Multi-modal Neural Receiver for 6G Vehicular Communication
Osama Saleem, Mohammed Alfaqawi, Pierre Merdrignac +2
Deep Learning (DL) based neural receiver models are used to jointly optimize PHY of baseline receiver for cellular vehicle to everything (C-V2X) system in next generation (6G) comm…
Large Language Model-Based Semantic Communication System for Image Transmission
Soheyb Ribouh, Osama Saleem
The remarkable success of Large Language Models (LLMs) in understanding and generating various data types, such as images and text, has demonstrated their ability to process and ex…
TransRx-6G-V2X : Transformer Encoder-Based Deep Neural Receiver For Next Generation of Cellular Vehicular Communications
Osama Saleem, Soheyb Ribouh, Mohammed Alfaqawi +2
End-to-end wireless communication is new concept expected to be widely used in the physical layer of future wireless communication systems (6G). It involves the substitution of tra…