Object detection is one of the most fundamental and challenging tasks to locate objects in
images and videos. Over the past, it has gained much attention to do more research on …

Multi-view learning is an emerging direction in machine learning which considers learning
with multiple views to improve the generalization performance. Multi-view learning is also …

Variations in the appearance of a tracked object, such as changes in geometry/photometry,
camera viewpoint, illumination, or partial occlusion, pose a major challenge to object …

Face images appearing in multimedia applications, eg, social networks and digital
entertainment, usually exhibit dramatic pose, illumination, and expression variations …

Convolutional neural networks (CNNs) have been successfully applied to the single target
tracking task in recent years. Generally, training a deep CNN model requires numerous …

Visual tracking using multiple features has been proved as a robust approach because
features could complement each other. Since different types of variations such as …

Conventional visual ship tracking methods employ single and shallow features for the ship
tracking task, which may fail when a ship presents a different appearance and shape in …

In multi-object tracking, it is critical to explore the data associations by exploiting the
temporal information from a sequence of frames rather than the information from the …

Recent advances in visual tracking have witnessed the importance of discriminative
classifiers tasked with distinguishing the target from the background. However, a single …

Understanding the progression of chronic diseases can empower the sufferers in taking
proactive care. To predict the disease status in the future time points, various machine …