Ph.D Theses

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Ph.D Theses

The blood vessels of the brain and the retina share common embryological origins and have comparable anatomy and physiology. In this thesis, patients with Schizophrenia (SCZ) and Bipolar disorder (BD) were recruited and compared with healthy volunteers (HV). We examined the diameters of the retinal venules and arterioles for abnormalities in patients and HV. 

The human visual system has a unique ability to conceptualizing the dynamics of objects' interactions in a scene. We are not only able to detect objects' motion (including articulated and deformable ones, such as humans and animals) in a given scene but also distinguish different types of motion patterns in their bodies during various interactive actions.

The use of machine-learning for multimedia forensics is gaining more and more consensus, especially due to the amazing possibilities offered by modern machine learning techniques. By exploiting deep learning tools, new approaches have been proposed whose performance remarkably exceed those achieved by state-of-the-art methods based on standard machine-learning and model-based techniques. 

In this era of stress-filled life styles and cut-throat competitions, cardiovascular diseases and heart abnormalities are becoming common in the people of early age groups.

Image filtering is a fundamental task in computer vision and image processing. Various linear and nonlinear filters are routinely used for enhancement, superresolution, sharpening, restoration, etc. The focus of this thesis is on kernel-based filtering that has received significant attention in recent years.

Matching images to a discrete camera is of significance in forensic investigation. In the case of digital images, forensic matching is possible through the use of sensor noise present within every image. There exist misconceptions, however, around how this noise reacts under variables such as temperature and the use of different lens systems.

With the great endeavor of computer vision community, 2D human pose estimation has achieved considerable success in recent years, from the introduction of single-person pose estimation models such as the convolutional pose machine and stacked hourglass models  to multi-person pose estimation networks such as OpenPose.


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