Autoimmune Diseases (AD) are among the top 10 leading causes of death in female
children and women in all age groups up to 64 years. They are widely diagnosed by various …

Sparse decomposition has been widely used for different applications, such as source
separation, image classification, image denoising and more. This paper presents a new …

Heating, Ventilating and Air Conditioning units (HVAC) are a major electrical energy
consumer in buildings. Monitoring of the operation and energy consumption of HVAC would …

Sparsity constrained single image super-resolution has been of much recent interest. A
typical approach involves sparsely representing patches in a low-resolution (LR) input …

Subspace learning is an important problem, which has many applications in image and
video processing. It can be used to find a low-dimensional representation of signals and …

Robust object tracking has widespread applications in human motion analysis systems, but
it is challenging due to various factors, such as occlusion, illumination variation, and …

In this paper, we propose a new joint dictionary learning method for example-based image
super-resolution (SR), using sparse representation. The low-resolution (LR) dictionary is …

The next generation of the electricity grid, also known as 'Smart Grid', is one of the most
complex cyber-physical systems (CPS) due to its extreme dimension, geographic reach, and …

Adaptive tracking-by-detection approaches are popular for tracking arbitrary objects. They
treat the tracking problem as a classification task and use online learning techniques to …

A discriminative ensemble tracker employs multiple classifiers, each of which casts a vote on
all of the obtained samples. The votes are then aggregated in an attempt to localize the …