In this paper we present a novel framework for generic object class detection by integrating Kernel PCA with AdaBoost. The classifier obtained in this way is invariant to changes...
Current feature-based methods for sketch recognition systems rely on human-selected features. Certain machine learning techniques have been found to be good nonlinear features ext...
We present in this paper a novel approach for shape description based on kernel principal component analysis (KPCA). The strength of this method resides in the similarity (rotatio...
Learning models for detecting and classifying object categories is a challenging problem in machine vision. While discriminative approaches to learning and classification have, in...
During the last years, the use of string kernels that compare documents has been shown to achieve good results on text classification problems. In this paper we introduce the appl...