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Home / programming language / Online Matlab Projects / Performance Optimization and Comparative Analysis of Neural Networks for Handwritten Devanagari Character Recognition
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Performance Optimization and Comparative Analysis of Neural Networks for Handwritten Devanagari Character Recognition

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SKU: PROJ7574 Categories: 2017 Projects, Final Year Projects, Digital Image Processing Projects, programming language, Online Matlab Projects Tags: Android Project, Asp.Net Project, C# Project, Computer Engineering Final Year Projects, Computer Science Final Year Projects, Electronics Projects Engineering Students Final Year, Engineering Student Project Ideas, Final Semester Projects, Final Year Project Center, Final Year Projects, ieee ECE Projects, ieee EEE Projects, ieee Final Year Projects, IEEE Projects, ieee Projects Networking, Image Processing Projects, J2EE Project, Java Project, Java Project Code, Matlab Project, PHP Project, Students Projects
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Performance Optimization and Comparative Analysis
of Neural Networks for Handwritten Devanagari
Character Recognition

Abstract— Devanagari script has character set with rich structural features that makes the recognition of unconstrained handwritten Devanagari characters difficult However, these features can be used to divide the characters into different categories. This paper presents few techniques for optimizing the recognition accuracy at pre-classification stage, feature extraction stage and recognition stage. Initially, the reclassification of the characters is done into different classes using various structural features. Then features are extracted using
optimized feature extraction techniques. Finally, the recognition is done using neural network. In this paper, different neural networks are implemented and their performances are analyzed < final year projects >

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