Deep learning uses stacks of multiple processing layers to learn representations of data with different levels of abstraction. It enables machines to have the understand[...]

Abstract This article describes a technique to augment a typical RGBD sensor by integrating depth estimates obtained via Structure-from-Motion (SfM) with depth measuremen[...]

There has been an ever growing interest in leveraging state of the art deep learning techniques for tracking objects in video frames. Such works primarily focus on using [...]

This dissertation presents a comprehensive exploration of innovative approaches and systems at the intersection of edge computing, deep learning, and real-time video anal[...]

This thesis proposes "1D Convolution replacement layer ", a novel optimization for first convolution layer in CNN. This optimization enables edge friendly streaming acce[...]

The availability of OpenCL for FPGAs along with High-Level Synthesis tools have made them an attractive platform for implementing compute-intensive massively parallel app[...]

AI processing has been a big area of focus for the research community for quite some years. The growing computation capability of edge devices has allowed Computer Vision[...]

The use of video streaming has been growing rapidly in the recent years and has beenutilized in various applications. Many of these applications are latency sensitive, bu[...]

This research introduces and evaluates an advanced AI-enabled Smart Video Surveillance (SVS) system designed to enhance safety across community spaces such as educational[...]

This research investigates the intersection of applied statistics, machine learning, and healthcare to leverage the quantitative approaches as a means of improving patien[...]