Abstract. We present a survey of recent results concerning the theoretical and empirical performance of algorithms for learning regularized least-squares classifiers. The behavior ...
Hierarchical conditional random fields have been successfully applied to object segmentation. One reason is their ability to incorporate contextual information at different scales....
Xavier Boix, Josep M. Gonfaus, Joost van de Weijer...
Classification is a well-established operation in text mining. Given a set of labels A and a set DA of training documents tagged with these labels, a classifier learns to assign l...
Abstract. This paper deals with the classification of color video sequences using Markov Random Fields (MRF) taking into account motion information. The theoretical framework relie...
A novel sonar array for mobile robots is presented with applications to localization and mapping of indoor environments. The ultrasonic sensor localizes and classifies multiple ta...