We use cluster analysis as a unifying principle for problems from low, middle and high level vision. The clustering problem is viewed as graph partitioning, where nodes represent ...
The self-organising map (SOM) has been successfully employed as a nonparametric method for dimensionality reduction and data visualisation. However, for visualisation the SOM requ...
Using a radiosity method to estimate light inter-reflections within large scenes still remains a difficult task. The two main reasons are: (i) the computations entailed by the rad...
Daniel Meneveaux, Kadi Bouatouch, Gilles Subrenat,...
We have developed a threaded parallel data streaming approach using Logistical Networking (LN) to transfer multi-terabyte simulation data from computers at NERSC to our local anal...
Viraj Bhat, Scott Klasky, Scott Atchley, Micah Bec...
Abstract— Analyzing unknown data sets such as multispectral images often requires unsupervised techniques. Data clustering is a well known and widely used approach in such cases....