Abstract
We propose a method in this paper for handwritten digit recognition using optimized prototypes generated through learning and transformation. In this method a set of prototypes are obtained from tra.ining samples and mapped to a multi-layer neural network for optimization to improve their classification power. The new prototypes are then transformed geometrically to produce a larger set of prototypes for recognition of testing samples. The method has been verified to work well in experimental studies.
| Original language | English |
|---|---|
| Article number | 389578 |
| Pages (from-to) | II625-II628 |
| Journal | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
| Volume | 2 |
| DOIs | |
| Publication status | Published - 1994 |
| Externally published | Yes |
| Event | Proceedings of the 1994 IEEE International Conference on Acoustics, Speech and Signal Processing. Part 2 (of 6) - Adelaide, Aust Duration: 19 Apr 1994 → 22 Apr 1994 |
Bibliographical note
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