In this paper, we present a method to represent achromatic and chromatic image signals independently for content-based image indexing and retrieval for image database applications...
We propose an unsupervised, probabilistic method for learning visual feature hierarchies. Starting from local, low-level features computed at interest point locations, the method c...
In this paper we report on our natural language information retrieval (NLIR) project as related to the recently concluded 5th Text Retrieval Conference (TREC-5). The main thrust o...
Tomek Strzalkowski, Fang Lin, Jose Perez Carballo,...
Given a set of images of scenes containing multiple object categories (e.g. grass, roads, buildings) our objective is to discover these objects in each image in an unsupervised man...
Abstract— Previous work [1] shows that the movement representation in task spaces offers many advantages for learning object-related and goal-directed movement tasks through imit...