The graph convolutional network (GCN) shows effective performance in
electroencephalogram (EEG) emotion recognition owing to the ability to capture brain …

Object tracking has long been an active research topic in image processing and computer
vision fields with various application areas. For practical applications, the object tracking …

The tracker is a core component of the tracking algorithm, but it is difficult to identify the
object, which is a challenge to improve the tracking accuracy. This paper proposes a …

As an important application of the Internet of Things (IoT) devices, sentiment analysis has
been paid more attention with the rapid development of artificial intelligence. As a widely …

Multi-Object Tracking (MOT) is an integral part of any autonomous driving pipelines because
it produces trajectories of other moving objects in the scene and predicts their future motion …

In this work, we propose CNN based approaches for EEG classification which is acquired
from a visual perception task involving different classes of images. Our approaches involve …

Three-dimensional (3D) face recognition has become a trending research direction in both
industry and academia. However, traditional facial recognition methods carry high …

Object tracking is a complex issue in computer vision; despite fast motion and motion blur,
most relevant techniques have produced lesser performances. To overcome the complex …

In visual tracking, the target always undergoes appearance variations due to a variety of
challenging situations, such as deformation and rotation. In this paper, we propose the target …

In this paper, we propose a fast and accurate deep network-based object tracking method,
which combines feature representation, template tracking and foreground detection into a …