—This paper proposes a framework for single-image super-resolution. The underlying idea is to learn a map from input low-resolution images to target high-resolution images based ...
In this paper, we explore how to effectively create and use "instant mesh networks", i.e., wireless mesh networks that are dynamically deployed in temporary circumstances...
Bo Xing, Mayur Deshpande, Sharad Mehrotra, Nalini ...
Hierarchical clustering methods are widely used in various scientific domains such as molecular biology, medicine, economy, etc. Despite the maturity of the research field of hie...
We develop a supervised dimensionality reduction method, called Lorentzian Discriminant Projection (LDP), for feature extraction and classification. Our method represents the str...
Ranking is a fundamental operation in data analysis and decision support, and plays an even more crucial role if the dataset being explored exhibits uncertainty. This has led to m...