Knowledge-Based Intelligent Techniques in Character Recognition presents research results on intelligent character recognition techniques, reflecting the tremendous worldwide interest in the applications of knowledge-based techniques in this challenging field.
This resource will interest anyone involved in computer science, computer engineering, applied mathematics, or related fields. It will also be of use to researchers, application engineers and students who wish to develop successful character recognition systems such as those used in reading addresses in a postal routing system or processing bank checks.
Recognition of Handwritten Digits in the Real World by a Neocognitron - H. Shouno, K. Fukushima and M. Okada
Recognition of Rotated Patterns Using Neocognitron - S. Satoh, J. Kunoiwa, H. Aso and S. Miyuke
Soft Computing Approach to Hand-written Numeral Recognition - J. F. Baldwin, T. P. Martin, and O. Stylianidis
Handwritten Character Recognition Using an MLP - F. Sorbello, G. A. M. Gioiello, and S. Vitabile
Signature Verification Based on Fuzzy Genetic Algorithm - J. N. K. Liu, and G. S. K. Fung
Application of a Generic Neural Network to Handwritten Digit Classification - D. S. Banarse and A. Duller
High-speed Recognition of Handwritten Amounts On Italian Checks - B. Lazzerini, L. M. Reyneri , F. Gregoretti, and A. Mariani
Off-line Handwritten Word Recognition Using Hidden Markov Models - A. El-Yacoubi, R. Sabourin, M. Gilloux and C. Y. Suen
Off-line Handwriting Recognition with Context Dependent Fuzzy Rules - A. Malaviya, F. Ivancic, J. Balasubramaniam and L. Peters
License-plate Recognition - M. H. Brugge, J. A. G. Nijihuis, L. Spaanenburg, and J. H. Stevens