Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. We propose an approach based on One-Class Support ...
Discriminative learning techniques for sequential data have proven to be more effective than generative models for named entity recognition, information extraction, and other task...
This paper presents a new system for recognition, tracking and pose estimation of people in video sequences. It is based on the wavelet transform from the upper body part and uses ...
Philipp Zehnder, Esther Koller-Meier, Luc J. Van G...
A novel algorithm is proposed to learn pattern similarities for texture image retrieval. Similar patterns in di erent texture classes are grouped into a cluster in the feature spac...
This paper describes a pattern classification approach for detecting frontal-view faces via learning a decision boundary. The classification can be achieved either by explicit est...