In sequential decision making under uncertainty, as in many other modeling endeavors, researchers observe a dynamical system and collect data measuring its behavior over time. The...
A general and expressive model of sequential decision making under uncertainty is provided by the Markov decision processes (MDPs) framework. Complex applications with very large ...
In many applications, we monitor data obtained from multiple streaming sources for collective decision making. The task presents several challenges. First, data in sensor networks...
The extraction of contours using deformable models, such as snakes, is a problem of great interest in computer vision, particular in areas of medical imaging and tracking. Snakes ...
Akshaya Kumar Mishra, Paul W. Fieguth, David A. Cl...
In this paper, we address the problem of color image restoration. Here, we model the image as a Markov Random Field (MRF) and propose a restoration algorithm in a multiresolution ...
P. K. Nanda, K. Sunil Kumar, S. Ghokale, Uday B. D...