We present a class of statistical models for part-based object recognition that are explicitly parameterized according to the degree of spatial structure they can represent. These...
David J. Crandall, Pedro F. Felzenszwalb, Daniel P...
Abstract. When developing statistical models of normal brain perfusion, two questions are of crucial interest: How well does an atlas describe normality and how sensitive is it at ...
Abstract--This paper presents a new wavelet-based image denoising method, which extends a recently emerged "geometrical" Bayesian framework. The new method combines three...
Aleksandra Pizurica, Wilfried Philips, Ignace Lema...
Abstract. Fitness functions based on the Ising model are suited excellently for studying the adaption capabilities of randomised search heuristics. The one-dimensional Ising model ...
Nonparametric methods are widely applicable to statistical learning problems, since they rely on a few modeling assumptions. In this context, the fresh look advocated here permeat...