Combining multiple HONG networks for recognizing unconstrained handwritten numerals
Ajantha Sanjeewa Atukorale, Ponnuthurai Nagaratnam Suganthan · 2003
This paper describes our investigation into the neural gas (NG) network and the hierarchical overlapped architecture which allowed us to obtain an excellent recognition rate for the NIST SD3 database. By defining an implicit ranking scheme, we made the NG algorithm runs faster in its sequential implementation. The hierarchical overlapped architecture allowed us to obtain multiple classifications for each sample data. Since a multiple classifier system is a powerful tool for difficult pattern recognition problems, we developed three classifiers based on three different feature extraction methods, with global and structural features.