The term neural network evolution usually refers to network topology evolution leaving the network's parameters to be trained using conventional algorithms. In this paper we ...
Ioannis G. Tsoulos, Dimitris Gavrilis, Euripidis G...
Subspacefacerecognitionoftensuffersfromtwoproblems:(1)thetrainingsamplesetissmallcompared with the high dimensional feature vector; (2) the performance is sensitive to the subspace...
This paper addresses the problem of rotation estimation directly from images defined on the sphere and without correspondence. The method is particularly useful for the alignment ...
We introduce a new approach to the problem of collision detection in multi-axis NC-machining. Due to the directional nature (tool axis) of multi-axis NCmachining, space subdivisio...
Oleg Ilushin, Gershon Elber, Dan Halperin, Ron Wei...
This paper presents a real-time rendering pipeline for implicit surfaces defined by a regular volumetric grid of samples. We use a ray-casting approach on current graphics hardwar...
Markus Hadwiger, Christian Sigg, Henning Scharsach...