In this paper we present a method for the selection of training instances based on the classification accuracy of a SVM classifier. The instances consist of feature vectors repres...
Miguel Lopes, Fabien Gouyon, Alessandro Koerich, L...
In this paper we describe an online/incremental linear binary classifier based on an interesting approach to estimate the Fisher subspace. The proposed method allows to deal with ...
Alessandro Rozza, Gabriele Lombardi, Marco Rosa, E...
Abstract--Recently, classifier grids have shown to be a considerable alternative for object detection from static cameras. However, one drawback of such approaches is drifting if a...
Abstract. Trained support vector machines (SVMs) have a slow runtime classification speed if the classification problem is noisy and the sample data set is large. Approximating the...
Multi-class classification algorithms are very widely used, but we argue that they are not always ideal from a theoretical perspective, because they assume all classes are characte...