This paper presents a novel method for the classification of images that combines information extracted from the images and contextual information. The main hypothesis is that con...
In this paper we propose to combine two powerful ideas, boosting and manifold learning. On the one hand, we improve ADABOOST by incorporating knowledge on the structure of the dat...
A measure of stability for a wide class of pattern recognition algorithms is introduced to cope with overfitting in classification problems. Based on this concept, constructive me...
Classification is an important step towards fingerprint recognition. In the classification stage, fingerprints are usually associated to one of the five classes “A”, “L”, ...
Gian Luca Marcialis, Fabio Roli, Alessandra Serrau
Abstract. A tracking-by-detection framework is proposed that combines nearest-neighbor classification of bags of features, efficient subwindow search, and a novel feature selection...