We investigate when sparse coding of sensory inputs can improve performance in a classification task. For this purpose, we use a standard data set, the MNIST database of handwritte...
Classifying an unknown input is a fundamental problem in pattern recognition. A common method is to define a distance metric between patterns and find the most similar pattern i...
Sung-Hyuk Cha, Charles C. Tappert, Sargur N. Sriha...
In this paper, we propose a new prototype learning/matching method that can be combined with support vector machines (SVM) in pattern recognition. This hybrid method has the follo...
In this paper, a new method of composing a multiclass classifier using pairwise classifiers is proposed. A “Resemblance Model” is exploited to calculate a posteriori probabili...
This paper presents a genetic programming based approach for optimizing the feature extraction step of a handwritten character recognizer. This recognizer uses a simple multilayer ...