Bayesian statistical theory is a convenient way of taking a priori information into consideration when inference is made from images. In Bayesian image detection, the a priori dist...
This paper presents an integrated study on possible topological relationship between multidimensional simple objects in 0,1,2 and 3 D space. The formal categorisation of spatial r...
For discrete sets coded by the Freeman chain describing their contour, several linear algorithms have been designed for determining their shape properties. Most of them are based ...
Intrinsic curvature flows can be used to design Riemannian metrics by prescribed curvatures. This chapter presents three discrete curvature flow methods that are recently introduce...
Xiaotian Yin, Miao Jin, Feng Luo 0002, Xianfeng Da...
In this paper we propose a novel method for learning a Mahalanobis distance measure to be used in the KNN classification algorithm. The algorithm directly maximizes a stochastic v...
Jacob Goldberger, Sam T. Roweis, Geoffrey E. Hinto...