Transfer learning (TL) has been successfully applied to many real-world problems that
traditional machine learning (ML) cannot handle, such as image processing, speech …

The Internet of Things (IoT) is becoming an indispensable part of everyday life, enabling a
variety of emerging services and applications. However, the presence of rogue IoT devices …

Medical image processing is one of the most important topics in the Internet of Medical
Things (IoMT). Recently, deep learning methods have carried out state-of-the-art …

Deep learning (DL) has been utilized pervasively in the Internet of Things (IoT). One typical
application of DL in IoT is device identification from wireless signals, namely …

Recently, pre-trained deep learning (DL) models have been employed to tackle and
enhance the performance on many tasks such as skin cancer detection instead of training …

As one of the effective ways of ocular disease recognition, early fundus screening can help
patients avoid unrecoverable blindness. Although deep learning is powerful for image …

In the past decades, information from all kinds of data has been on a rapid increase. With
state-of-the-art performance, machine learning algorithms have been beneficial for …

Semantic segmentation of remote sensing images plays a vital role in land resource
management, yield estimation, and economic evaluation. Therefore, this paper proposes a …

Recently, urbanization becomes a major concern for develo** as well as developed
countries. Owing to the increased urbanization, one of the important challenging issues in …

The management of motor complications in Parkinson's disease (PD) is an unmet need. This
paper proposes an eHealth platform for Parkinson's disease (PD) severity estimation using a …