Research Article
Vishal Mourya · Mrs. Aradhana Singh
Journal
International Journal of Digital Applications and Contemporary Research (IJDACR)
ISSN
2319-4863
Volume / Issue
Vol.5 · Issue 2
Published
September 2016
Access
Open Access
Licence
CC BY-NC-SA 4.0
The selection of features is an important step in any pattern recognition system. This selection of features is considered a combinatorial optimization problem and made the object of research in many disciplines. The main objective of the selection of features is to reduce the number of them by eliminating redundant and irrelevant features recognition system. The second objective of this feature selection is also to maintain and / or improve the performance of the classifier used by the recognition system. In this paper, Genetically Optimized Neural Network (GA-NN) algorithm is used to solve this type of feature selection problem in the recognition of character. The results in the selection of features have reduced the complexity of using GA-NN approach.
Vishal Mourya, Mrs. Aradhana Singh (2016). Hybrid Feature Extraction for Character Recognition using Genetically Optimized Neural Network. International Journal of Digital Applications and Contemporary Research (IJDACR), Vol.5, Issue 2. ISSN: 2319-4863.
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