Abstract
The neocognitron, which is proposed based on the model of biological vision, has been acclaimed as a shift and distortion tolerant character recognition system. Unfortunately, studies show that the performance of the neocognitron is affected greatly by the value of its selectivity. The neocognitron has a poor recognition rate if the value of selective is not reasonable. A genetic algorithm based method for adjusting necognitron selectivity is proposed. By using the proposed method, the responses of 5-plane are uniform. The proposed method is tested on 10 digits, and the simulation results show that it is capable of improving the recognition rate of neocognitron.
| Original language | English |
|---|---|
| Pages (from-to) | 1665-1668 |
| Number of pages | 4 |
| Journal | Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology |
| Volume | 38 |
| Issue number | 10 |
| State | Published - Oct 2006 |
| Externally published | Yes |
Keywords
- Genetic algorithm
- Neocognitron
- Selectivity
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