The emergence of Tiny Machine Learning (TinyML) has positively revolutionized the field of
Artificial Intelligence by promoting the joint design of resource-constrained IoT hardware …

The emerging field of artificial intelligence of things (AIoT, AI+ IoT) is driven by the
widespread use of intelligent infrastructures and the impressive success of deep learning …

Edge computing has gained significant traction in recent years, promising enhanced
efficiency by integrating artificial intelligence capabilities at the edge. While the focus has …

Unmanned Aerial Vehicles (UAVs) have gained increasing attention by both academic and
industrial communities, due to their flexible deployment and efficient line-of-sight …

With the rapid development of renewable energy and the increasing maturity of energy
storage technology, microgrids are quickly becoming popular worldwide. The stochastic …

Data collected by IoT devices are often private and have a large diversity across users.
Therefore, learning requires pre-training a model with available representative data …

Meta-learning has been widely used in medical image analysis. However, it requires a large
amount of storage space and computing resources to train and use neural networks …

Artificial Intelligence of Things (AIoT) has recently accepted significant interests.
Remarkably, embedded artificial intelligence (eg, deep learning) on-device transforms IoT …

The lottery ticket hypothesis (LTH) states that a randomly initialized dense network contains
sub-networks that can be trained in isolation to the performance of the dense network. In this …

With the world heading towards big data, insurmountable amounts of data are being
generated from Internet of Things devices around the world. Within the healthcare paradigm …