An important strength of learning classifier systems (LCSs) lies in the combination of genetic optimization techniques with gradient-based approximation techniques. The chosen app...
Martin V. Butz, Pier Luca Lanzi, Stewart W. Wilson
In this research, an iterative and unsupervised Turbo-style algorithm is presented and implemented for the task of automatic lexical acquisition. The algorithm makes use of spoken...
Ghinwa F. Choueiter, Mesrob I. Ohannessian, Stepha...
This paper presents a novel approach for designing a semi-automatic adaptive OCR for large document image collections in digital libraries. We describe an interactive system for co...
Sachin Rawat, K. S. Sesh Kumar, Million Meshesha, ...
Feature selection is used to improve performance of learning algorithms by finding a minimal subset of relevant features. Since the process of feature selection is computationally ...
Mark Last, Abraham Kandel, Oded Maimon, Eugene Ebe...
- This paper demonstrates how methods borrowed from information fusion can improve the performance of a classifier by constructing (i.e., fusing) new features that are combinations...