The performance of any deep learning model depends heavily on the quantity and quality of the available training data. The generalization of the trained deep models improves with the availability of a large number of ...

Traditional strategies to build machine learning based classification systems employ discrete labels as targets. This limits the usefulness of such systems in two ways. First, the generalizability of these systems is limited ...

Deep Neural Networks (DNNs) have had a significant impact on a wide variety of domains, such as Autonomous Vehicles, Smart Cities, and Healthcare, through low-latency inferencing on edge computing devices close to the data ...