Caused by the rising of new network types, eg, Internet of Things (IoT), within the last
decade and related challenges like Big Data and data processing delay, new paradigms …

In recent years, deep learning (DL) models have demonstrated remarkable achievements
on non-trivial tasks such as speech recognition, image processing, and natural language …

EdgeAI (Edge computing based Artificial Intelligence) has been most actively researched for
the last few years to handle variety of massively distributed AI applications to meet up the …

Serverless computing has become a popular part of the cloud computing model, thanks to
abstracting away infrastructure management and enabling developers to write functions that …

With the emergence of AI regulations, such as the EU AI Act, requirements for simple data
lineage, enforcement of low data bias, and energy efficiency have become a priority for …

Benchmarking deep learning algorithms before deploying them in hardware-constrained
execution environments, such as imaging satellites, is pivotal in real-life applications …

Edge AI is one of the newly emerged application domains where networked IoT (Internet of
Things) devices are deployed to perform AI computations at the edge of the cloud …

Due to the development of small-size, energy-efficient, and powerful CPUs and GPUs for
single board computers, various edge devices are widely adopted for hosting real-world …

With the rapid development of wireless communication technology and the emergence of
intelligent applications, higher requirements have been put forward for data communication …

As the next generation of diverse workloads like autonomous driving and augmented/virtual
reality evolves, computation is shifting from cloud-based services to the edge, leading to the …