Abstract
This paper describes an efficient neuro-fuzzy method for recognizing on-line handwriting characters. The basic idea is to train a number of network classifiers and aggregating them with fuzzy logic. The method combines the outputs of separate networks with importance of each network, which is subjectively assigned as the nature of fuzzy logic. We demonstrate the superior performance of the presented method and compare with conventional methods like voting and averaging by thorough experiments on a difficult on-line handwriting recognition problem.
| Original language | English |
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| Pages | 1131-1136 |
| Number of pages | 6 |
| Publication status | Published - 1995 |
| Event | Proceedings of the 1995 IEEE International Conference on Fuzzy Systems. Part 1 (of 5) - Yokohama, Jpn Duration: 1995 Mar 20 → 1995 Mar 24 |
Other
| Other | Proceedings of the 1995 IEEE International Conference on Fuzzy Systems. Part 1 (of 5) |
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| City | Yokohama, Jpn |
| Period | 95/3/20 → 95/3/24 |
All Science Journal Classification (ASJC) codes
- Software
- Theoretical Computer Science
- Artificial Intelligence
- Applied Mathematics