—This paper addresses the problem of self-validated labeling of Markov random fields (MRFs), namely to optimize an MRF with unknown number of labels. We present graduated graph c...
We introduce a new graph-theoretic approach to image segmentation based on minimizing a novel class of `mean cut' cost functions. Minimizing these cost functions corresponds ...
A discrete regularization framework on graphs is proposed and studied for color image filtering purposes when images are represented by grid graphs. Image filtering is considered...
We propose a discrete regularization framework on weighted graphs of arbitrary topology, which unifies image and mesh filtering. The approach considers the problem as a variation...
This paper suggests dense and switched modular primitives for a bond-graph-based GP design framework that automatically synthesizes designs for multi-domain, lumped parameter dynam...
Kisung Seo, Zhun Fan, Jianjun Hu, Erik D. Goodman,...