This paper describes a unified approach, based on Gaussian Processes, for achieving sensor fusion under the problematic conditions of missing channels and noisy labels. Under the ...
Abstract. This paper deals, for the first time, with an analysis of localization capabilities of weakly supervised categorization systems. Most existing categorization approaches ...
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
Abstract. This paper proposes a novel method to deal with the representation issue in texture classification. A learning framework of image descriptor is designed based on the Fish...
Supervised learning uses a training set of labeled examples to compute a classifier which is a mapping from feature vectors to class labels. The success of a learning algorithm i...