We show that for even quasi-concave objective functions the worst-case distribution, with respect to a family of unimodal distributions, of a stochastic programming problem is a u...
Abstract—A general variational framework for image approximation and segmentation is introduced. By using a continuous “line-process” to represent edge boundaries, it is poss...
There are p heterogeneous objects to be assigned to n
competing agents (n > p) each with unit demand. It is
required to design a Groves mechanism for this assignment
problem ...
In this paper we propose a novel prior-based variational object segmentation method in a global minimization framework which unifies image segmentation and image denoising. The id...
Anders Heyden, Christian Gosch, Christoph Schn&oum...
We describe an approach to understanding evolved programs for a real world object detection problem, that of finding orthodontic landmarks in cranio-facial X-Rays. The approach in...
Victor Ciesielski, Andrew Innes, Sabu John, John M...