Modeling spatiotemporal global dependencies and dynamics of body joints are crucial to
recognizing actions from 3D skeleton sequences. We propose a Relation-mining Self …

This research investigates the recognition of basketball techniques actions through the
implementation of three-dimensional (3D) Convolutional Neural Networks (CNNs), aiming to …

This paper proposes an improved target detection algorithm, SDE-YOLO, based on the
YOLOv5s framework, to address the low detection accuracy, misdetection, and leakage in …

Action recognition, a vital subfield of computer vision, profoundly enhances security, health,
and human–computer interaction through its sophisticated analytical capabilities. The …

Benefiting from the advanced human visual system, humans naturally classify activities and
predict motions in a short time. However, most existing computer vision studies consider …

With the increasing incidence of autism spectrum disorders (ASDs), the physical and mental
status of patients and the economic burden on their families have become a major concern …

Unmanned aerial vehicles (UAVs) equipped with remote-sensing object-detection devices
are increasingly employed across diverse domains. However, the detection of small …

Understanding human actions from body poses is critical for assistive robots sharing space
with humans in order to make informed and safe decisions about the next interaction …

Skeleton-based human recognition is a key technology for visual feedback, which can help
the Internet of Things (IoT) interact with humans in a non-contact manner outdoors. Graph …

In recent years, it has been a commonly adopted strategy to transform categorical data into
numerical one to suit popular learning approaches, such as neural networks. The above …