This paper proposes a novel hierarchical learning strategy to deal with the data sparseness problem in relation extraction by modeling the commonality among related classes. For e...
Microarray datasets are often too large to visualise due to the high dimensionality. The self-organising map has been found useful to analyse massive complex datasets. It can be us...
— We present a new retraction algorithm for high DOF articulated models and use our algorithm to improve the performance of RRT planners in narrow passages. The retraction step i...
This paper considers the problem of automatic classification of textured tissues in 3D MRI. More specifically, it aims at validating the use of features extracted from the phase of...
Jurgen Fripp, Peter Stanwell, Pierrick Bourgeat, S...
This paper focuses on the retrieval of complex images based on their textural content. We use GMRF for texture discrimination and a region-growing algorithm for texture segmentati...
Eugenio Di Sciascio, Giacomo Piscitelli, Augusto C...