Rationale/importance Researches have highlighted communication deficits between resting-
state brain networks in major depressive disorder (MDD), as reflected in abnormal functional …

The trend of the era of the Internet of Everything has promoted the integration of various
industries and the Internet of Things (IoT) technology, and the scope of influence of the IoT is …

Action recognition via 3D skeleton data is an emerging important topic. Most existing
methods rely on hand-crafted descriptors to recognize actions, or perform supervised action …

According to the WHO, the number of mental disorder patients, especially depression
patients, has overgrown and become a leading contributor to the global burden of disease …

Human action recognition has been applied in many fields, such as video surveillance and
human computer interaction, where it helps to improve performance. Numerous reviews of …

We focus on unsupervised representation learning for skeleton based action recognition.
Existing unsupervised approaches usually learn action representations by motion prediction …

Medical image segmentation methods downsample images for feature extraction and then
upsample them to restore resolution for pixel-level predictions. In such schema, upsample …

In recent years, major depressive disorder (MDD) has been shown to negatively impact
physical recovery in a variety of patients. Functional near-infrared spectroscopy (fNIRS) is a …

Skeleton-based action recognition has attracted significant attention and obtained
widespread applications due to the robustness of 3D skeleton data. One of the key …

Self-supervised representation learning has proven constructive for skeleton-based action
recognition. For better performance, existing methods mainly focus on 1) multi-modal data …