The skeleton-based action recognition technology can effectively avoid the background
interference and occlusion problems in the image. However, the recognition of similar …

Abstract Directed Graph convolutional networks (DGCNs) have been indeed gaining
attention and being applied in skeleton-based action recognition tasks to capture the …

Recently, mobile data and traffic growth pushed mobile operators and service providers to re-
engineer the core mobile network and deliver salable solutions through several solutions …

Recently, there has been a surge of interest in utilizing Graph Convolutional Networks
(GCNs) for skeleton-based action recognition, where learning effective representations of …

Lately, there has been a surge in interest in utilizing Graph Convolutional Networks (GCNs)
for the purpose of action recognition using skeletal data. In order to achieve optimal results …

Human action recognition has recently attracted much attention in computer vision research.
Its applications are widely found in video surveillance, human-computer interaction …

Surveillance systems are essential for social and personal security. However, monitoring
multiple video feeds with multiple targets is challenging for human operators. Therefore …

Session-based recommendation (SBR) predicts the next interaction of users based on their
clicked items in a session. Previous studies have shown that hypergraphs are superior in …

Entity alignment is an important task in Knowledge Graph (KG), which aims to find identical
entities in two different KGs. Existing methods include two steps, graph representation and …

Skeletal behavior recognition provides a valuable method to understand the intricacies of
human action and can handle the semantic gap relationships between physical constraints …