Many state-of-the-art object recognition systems rely on identifying the location of objects in images, in order to better learn its visual attributes. In this paper, we propose fo...
The major contribution of this paper is the presentation of a general unifying description of distributed algorithms allowing to map local, node-based, algorithms onto a single gl...
A novel approach is proposed that extends the classical background subtraction method to extract silhouettes from videos in real time with dynamic viewpoint variation caused by ca...
We show how cultural selection for learnability during the process of linguistic evolution can be visualized using a simple iterated learning model. Computational models of linguis...
This paper presents a new framework for anytime heuristic search where the task is to achieve as many goals as possible within the allocated resources. We show the inadequacy of t...