Multiple Classifier System for Offline Malayalam Character Recognition
| Autor: | Anitha Mary M. O. Chacko, P. M. Dhanya |
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| Rok vydání: | 2015 |
| Předmět: |
Scheme (programming language)
Artificial neural network Computer science business.industry Speech recognition Gradient feature Pattern recognition Character Recognition language.human_language ComputingMethodologies_PATTERNRECOGNITION and Neural Networks Malayalam language Feature (machine learning) Multiple Classifier System General Earth and Planetary Sciences Feedforward neural network Artificial intelligence business Density feature computer General Environmental Science computer.programming_language |
| Zdroj: | Procedia Computer Science. 46:86-92 |
| ISSN: | 1877-0509 |
| Popis: | This paper presents a multiple classifier system for the recognition of offline handwritten Malayalam characters. The features used are the gradient and density based features. These feature sets are fed as input to two feedforward neural networks. The results of both these neural networks are combined using four different combination schemes: Max rule, Sum rule, Product rule and Borda count method. The best combination ensemble with an accuracy of 81.82% is obtained by using the Product rule combination scheme. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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