Applications in the Internet of Things (IoT) utilize machine learning (ML) to analyze sensor-
generated data. However, a major challenge lies in the lack of targeted intelligence in …

Abstract Knowledge Graphs (KGs) have become a pivotal knowledge representation tool in
machine learning, not only providing access to existing knowledge but also enabling the …

With the increasing integration of machine learning into IoT devices, managing energy
consumption and data transmission has become a critical challenge. Many IoT applications …

Due to the rapidly evolving landscape of cybersecurity, the risks in securing cloud networks
and devices are attesting to be an increasingly prevalent research challenge. Reinforcement …

Hyperdimensional computing (HDC) is an emerging computing paradigm with significant
promise for efficient and robust learning. In HDC, objects are encoded with high …

During the advancement of modern deep learning algorithms, models become increasingly
demanding in computing resources and power-hungry, such that they are considered less …

Detecting marine objects inshore presents challenges owing to algorithmic intricacies and
complexities in system deployment. We propose a difficulty-aware edge-cloud collaborative …

The recent advances in Deep Learning (DL) have changed the landscape of Machine
Learning significantly. However, over the last few years, we observe that to enable complex …