We describe an algorithm for converting linear support vector machines and any other arbitrary hyperplane-based linear classifiers into a set of non-overlapping rules that, unlike...
Linear Discriminant Analysis(LDA) is widely-used in face recognition systems. However, with the traditional formulation, the available information in the training samples is not su...
In this paper, we propose classifier ensemble selection for Named Entity Recognition (NER) as a single objective optimization problem. Thereafter, we develop a method based on gen...
Abstract. Image fusion in high-resolution aerial imagery poses a challenging problem due to fine details and complex textures. In particular, color image fusion by using virtual or...
Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) techniques are important and well-developed area of image recognition and to date many linear discriminati...