Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
We propose a method to construct computer vision systems using a workbench composed of a multi-faceted toolbox and a general purpose kernel. The toolbox is composed of an open set ...
In this article, a novel concept is introduced by using both unsupervised and supervised learning. For unsupervised learning, the problem of fuzzy clustering in microarray data as ...
Currently the best algorithms for transcription factor binding site prediction are severely limited in accuracy. In previous work we combine random selection under-sampling with th...
Yi Sun, Mark Robinson, Rod Adams, Rene te Boekhors...
In this paper, we propose a novel patch-based face hallucination framework, which employs a dual model to hallucinate different components associated with one facial image. Our mod...