Studies show lots of advanced research on various data types such as image, speech, and
text using deep learning techniques, but nowadays, research on video processing is also an …

Accurate and robust visual object tracking is one of the most challenging and fundamental
computer vision problems. It entails estimating the trajectory of the target in an image …

Background Image-based tracking of individual animals can provide rich data to underpin
breakthroughs in biological and medical research, but few if any existing methods extend to …

Federated Learning is a novel framework that allows multiple devices or institutions to train a
machine learning model collaboratively while preserving their data private. This …

Single-object tracking is a well-known and challenging research topic in computer vision.
Over the last two decades, numerous researchers have proposed various algorithms to …

Feature Selection Library (FSLib) is a widely applicable MATLAB library for Feature
Selection (FS). FS is an essential component of machine learning and data mining which …

Tiny objects, frequently appearing in practical applications, have weak appearance and
features, and receive increasing interests in many vision tasks, such as object detection and …

With the widespread use of deep learning in single object tracking task, mainstream tracking
algorithms treat tracking as a combined classification and regression problem. Classification …

The discriminative correlation filter (DCF) is one of the crucial visual tracking methods, and it
has outstanding performance. Nevertheless, DCF-based methods have an unavoidable …

Recently, object tracking have achieved remarkable progress in terms of both efficiency and
accuracy. However, exiting methods still cannot satisfy challenging tasks under complicated …