Several new goodness-of-fit tests are proposed on countable alphabets, where certain fundamental statistical concepts associated with random variables, such as cumulative[...]

The prevalence of electrical fires due to arc faults in both AC and DC systems has necessitated advancements in detection technologies. This dissertation introduces innov[...]

The need for autonomous vehicles that do not operate on highways and can move off-road is increasing. While there have been significant advancements in autonomous passeng[...]

Localization and communication are critical components for functioning autonomous robots. The infrastructure required or these operations commonly includes global positio[...]

Recent advances in Deep Learning have made possible distributed multi-camera IoT vision analytics targeted at a variety of surveillance applications involving automated r[...]

Vision based Activity Detection is concerned with the automatic extraction, analysis and understanding of useful information from a sequence of images. It involves the de[...]

Single image depth estimation has always been a key interest in computer visioncommunity. Although depth estimation from a single monocular image still is anill-posed pr[...]

Object detection in high-resolution aerial images is a challenging task because of1) the large variation in object size, and 2) non-uniform distribution of objects. A com[...]

This report motivates the roles of Cloud computing, Edge computing, and thehierarchically distributed cooperative Fog computing, for the real-time analysis ofbig-data in [...]

This thesis proposes a novel method to recover depth of scene objects using an acoustic source and a calibrated neuromorphic camera or event camera sensor. The proposed s[...]