With the advent of big data, graphs have gained popularity as one of the most efficient data storage mechanisms. A graph can not only capture relationships between entities, but it can also store attributes associated with ...

With the increase in demand for high-speed connectivity, millimeter-wave (mmwave) communication has received increasing attention from academia and industry due to its exceptional advantages. Compared to existing wireless ...

Egocentric videos are recorded in a hands-free, always-on, under enhanced privacy-sensitive scenario and are often collected from day to weeks. For efficient consumption, such videos require robust video analysis techniques ...

Correlation Filter based visual trackers have demonstrated tremendous progress in object tracking. These trackers primarily use hierarchical features learned from multiple layers of a deep network. However, issues related ...

Most of the current wireless networks are radio frequency (RF) based, however, these networks are regularly confronted with growing demand for higher data rates. Watching high-definition live stream videos and accessing ...

Non-Intrusive Load Monitoring (NILM), also known as Energy Disaggregation, is the process of segregating a building’s total electricity consumption into its appliances by appliance consumption from the smart meter data. ...

Time series analytics is the practice of determining future values of correlated signals. In seminal works, time series were modeled using classical techniques such as ARMA (autoregressive moving average), and its variants ...

Transportation is a fundamental task in modern-day civilization. Examples of transportation in our daily lives include going to the workplace, returning home after work, etc. In this thesis, we investigate computational ...

Due to the enormous number of cellular users, the traffic load on the core network is increasing rapidly. Hence, it is difficult to maintain the required quality of service in the cellular network. Further, the normal ...

This thesis, “Deep Learning Assisted Methods for Microscopic Blood Cancer Imaging Analysis” aims to develop deep learning-based CAD tools for Acute Lymphoblastic Leukemia (ALL) and Multiple Myeloma (MM). A CAD tool typically ...