Beyond KernelBoost
Published in arXiv (Cornell University) • Jul 28, 2014
NobleIDNI6P71W62R93S46
Authors:,,
Roberto Rigamonti
Vincent Lepetit
Pascal Fua
Abstract
In this Technical Report we propose a set of improvements with respect to the KernelBoost classifier presented in [Becker et al., MICCAI 2013]. We start with a scheme inspired by Auto-Context, but that is suitable in situations where the lack of large training sets poses a potential problem of overf...
Finding related papers...
Discussions
(0)No comments yet
Be the first to share your thoughts!