The scoring of sleep stages is one of the essential tasks in sleep analysis. Since a manual
procedure requires considerable human and financial resources, and incorporates some …

Sleep staging has a very important role in diagnosing patients with sleep disorders. In
general, this task is very time-consuming for physicians to perform. Deep learning shows …

To effectively address air pollution and enhance air quality, governments must be able to
predict the air quality index with high accuracy and reliability. However, air quality prediction …

Existing automatic sleep stage classification systems have mostly relied on hand-crafted
features selected from polysomnographic records. To measure the quality of sleep, the …

In recent years, deep learning has shown potential and efficiency in a wide area including
computer vision, image and signal processing. Yet, translational challenges remain for user …

Automated sleep stages classification facilitates clinical experts in conducting treatment for
sleep disorders, as it is more time-efficient concerning the analysis of whole-night …

To generate a machine learning model to solve real-world problems, analysis of how the
model is actually learned and predicted from data is now essential for solving practical …