AdaBoost rarely suffers from overfitting problems in low noise data cases. However, recent studies with highly noisy patterns clearly showed that overfitting can occur. A natural s...
This paper proposes a method for constructing a discriminative rotation invariant object recognition system from the set of complex moments by using a multi-class boosting algorit...
This paper proposes a method for sign language recognition that bypasses the need for tracking by classifying the motion directly. The method uses the natural extension of haar li...
Learning from ambiguous training data is highly relevant in many applications. We present a new learning algorithm for classification problems where labels are associated with se...
In this paper, we present a novel iris recognition method based on learned ordinal features.Firstly, taking full advantages of the properties of iris textures, a new iris represen...