Machine learning models have made many decision support systems to be faster, more
accurate, and more efficient. However, applications of machine learning in network security …

There is significant enthusiasm for the employment of Deep Neural Networks (DNNs) for
important tasks in major wireless communication systems: channel estimation and decoding …

As the adoption of machine learning models increases, ensuring robust models against
adversarial attacks is increasingly important. With unsupervised machine learning gaining …

The new generation of wireless communication systems proposes the vision that artificial
intelligence should play a more significant role in the development of techniques, thus the …

Due to their robustness to degraded capturing conditions, radars are widely used for
environment perception, which is a critical task in applications like autonomous vehicles …

Machine Learning (ML) has been instrumental in enabling joint transceiver optimization by
merging all physical layer blocks of the end-to-end wireless communication systems …

The majority of streaming Internet of Things (IoT) applications use machine learning models
to identify and classify streaming inputs before forwarding them for further processing. These …

Machine Learning (ML) is becoming a cornerstone enabling technology for the next
generation of wireless systems. This is mainly due to the high performance achieved by …

Plusieurs méthodes traditionnelles sont utilisées pour sécuriser les données sensibles,
telles que les algorithmes de cryptographie comme AES-HMAC-SHA256, Twofish et …