We propose a new maximum margin discriminative learning algorithm here for classification of temporal signals. It is superior to conventional HMM in the sense that it does not nee...
Invariance is an important aspect in image object recognition. We present results obtained with an extended tangent distance incorporated in a kernel density based Bayesian classi...
Abstract. We describe and empirically evaluate machine learning methods for the prediction of zinc binding sites from protein sequences. We start by observing that a data set consi...
Sauro Menchetti, Andrea Passerini, Paolo Frasconi,...
In this paper we propose a classification-based method towards the segmentation of diffusion tensor images. We use Support Vector Machines to classify diffusion tensors and we ex...
In this paper, a multi-class classification system is developed for medical images. We have mainly explored ways to use different image features, and compared two classifiers: Pri...