BAYDOUN M.

Communication and information field has witnessed recent developments in wireless technologies. Among such emerging technologies, the Internet of Things (IoT) is gaining a lot of popularity and attention in almost every field. IoT devices have to be equipped with cognitive capabilities to enhance spectrum utilization by sensing and learning the...

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Anomaly detection constitutes a fundamental step in developing self-aware autonomous agents capable of continuously learning from new situations, as it enables to distinguish novel experiences from already encountered ones. This paper combines Dynamic Bayesian Networks (DBNs) and Neural Networks (NNs) and proposes a method for detecting...

Unmanned Aerial Vehicles (UAVs) attracted both industry and research community owing to their fascinating features like mobility, deployment flexibility and strong Line of Sight (LoS) links. The integration of Cognitive Radio (CR) can greatly help UAVs to overcome several issues especially spectrum scarcity. However, the dynamic radio...

Self-learning abilities in autonomous systems are essential to improve their situational awareness and detection of normal/abnormal situations. In this work, we propose a graph matching technique for activity detection in autonomous agents by using the Gromov-Wasserstein framework. A clustering approach is used to discretise continuous agents'...

We propose a probabilistic method to track and interpret the interactions of moving objects. The proposed method is based on the analysis of location data from different moving objects that modify their dynamics according to rules of interactions, namely attractive and repulsive forces governing objects' motions in a scene. Our method uses a...