This site uses cookies to deliver our services and to ensure you get the best experience. By continuing to use this site, you consent to our use of cookies and acknowledge that you have read and understand our Privacy Policy, Cookie Policy, and Terms
This paper presents a new semi-competitive learning paradigm named Competitive and Cooperative Learning (CCL), in which seed points not only compete each other for updating to ada...
In this paper we present a new method for fully automatic liver segmentation in computed tomography images. First, an initial set of seed points for the random walker algorithm is ...
Florian Maier, Andreas Wimmer, Grzegorz Soza, Jens...
Rival Penalized Competitive Learning (RPCL) and its variants can perform clustering analysis efficiently with the ability of selecting the cluster number automatically. Although t...
Tao Li, Wenjiang Pei, Shao-ping Wang, Yiu-ming Che...
We present a novel method for finding more good feature pairs between two sets of features. We first select matched features by Bi-matching method as seed points, then organize th...
This paper presents an hybrid segmentation technique that combines both the speed of an edge based approach with the robustness of a surface based approach. It consists of three s...