Application of the HLVQ neural network to hand-written digit recognition
B. Solaiman, Yvon Autret · 2002
In this work, the handwritten digit recognition problem is studied. Self organizing feature maps are mainly considered. The unsupervised Kohonen as well as the hybrid learning vector quantization (HLVQ) algorithms are applied. The main objective is to obtain a topology preserving map having high recognition rates. This is essentially due to the fact that this kind of maps is very useful in realising results interpretations and in the definition of a rejection strategy during the recognition phase.>