We introduce a new class of Reinforcement Learning algorithms designed to operate in perceptual spaces containing images. They work by classifying the percepts using a computer vi...
Bayesian statistical theory is a convenient way of taking a priori information into consideration when inference is made from images. In Bayesian image detection, the a priori dist...
Hardware square-root units require large numbers of gates even for iterative implementations. In this paper, we present four low-cost high-performance fullypipelined n-select impl...
In this paper we compare performance of several heuristics in generating informative generic/query-oriented extracts for newspaper articles in order to learn how topic prominence ...
—In the context of vehicular safety and entertainment applications, we focus on the design of a reliable medium access control scheme. Each vehicle is willing to form a network a...