This paper presents an efficient and homogeneous paradigm for automatic acquisition and recognition of nonparametric shapes. Acquisition time varies from linear to cubic in the nu...
Results of neural network learning are always subject to some variability, due to the sensitivity to initial conditions, to convergence to local minima, and, sometimes more dramat...
We present a novel algorithm for detection of certain types of unusual events. The algorithm is based on multiple local monitors which collect low-level statistics. Each local moni...
Amit Adam, Ehud Rivlin, Ilan Shimshoni, David Rein...
The blind source separation (BSS) problem is often solved by maximizing objective functions reflecting the statistical independence between outputs. Since global maximization may...
New techniques are presented for rendering complex hierarchical skeletal implicit models in several pen-and-ink styles. A particle system is employed to find interesting areas on ...
Kevin Foster, Pauline Jepp, Brian Wyvill, Mario Co...