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- W3204268601 abstract "Feature extraction is essential in the classification of handwritten character recognition. We have studied histogram of gradient (HOG) feature, local binary pattern (LBP), principal component analysis (PCA), and PCA can be used in feature extraction of Marathi handwritten compound character recognition. In feature extraction process, the data need to be reduced into a high dimensional space to a profound dimensional space. In feature selection, a subset of the primary set of features, or variables, get a modest subset which can be used to illustrate the problem." @default.
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- W3204268601 date "2021-01-01" @default.
- W3204268601 modified "2023-09-23" @default.
- W3204268601 title "Analysis of Feature Extraction Methods Used for Handwritten Marathi Compound Character Recognition" @default.
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- W3204268601 doi "https://doi.org/10.1007/978-981-33-6307-6_85" @default.
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