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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | A Comprehensive Analysis of Various Handwritten Character Recognition Techniques. |
| Authors Name: | Pankaj Kumar , Jyoti Kumari |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_213205
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| Published Paper Id: | IJNRD2402019 |
| Published In: | Volume 9 Issue 2, February-2024 |
| DOI: | |
| Abstract: | In this research, numerous strategies and procedures for neural network-based handwritten character recognition are presented. It includes a variety of methods used on scanned English characters, such as skeletonization, normalization, border detection, and feature extraction. describing the preprocessing, segmentation, and classification phases of the proposed system, it also explores a diagonal-based feature extraction technique for character recognition. Another strategy emphasizes binarization, segmentation, and neural network-based classification for character recognition without a feature extraction stage. The research also explores character recognition parameter adaption using neural networks' backpropagation technique and momentum approach. To detect handwritten English alphabet letters, it offers a hybrid technique that combines feature extraction and machine learning. A neural network approach to character identification is also discussed, along with its advantages and disadvantages when compared to more conventional pattern recognition techniques. The technique for English character recognition using multilayer perceptron networks is presented in the study, along with a discussion of the use of neural networks in handwritten character recognition (HCR) for banking. Overall, this study offers a thorough analysis of alternative neural network-based methods for reading handwritten characters, highlighting their advantages and potential uses in diverse scenarios. |
| Keywords: | Handwritten character recognition, Image Processing, Neural Network. |
| Cite Article: | "A Comprehensive Analysis of Various Handwritten Character Recognition Techniques.", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 2, page no.a135-a142, February-2024, Available :http://www.ijnrd.org/papers/IJNRD2402019.pdf |
| Downloads: | 000118758 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2402019 Registration ID: 213205 Published In: Volume 9 Issue 2, February-2024 DOI (Digital Object Identifier): Page No: a135-a142 Country: West champaran, bihar, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2402019 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2402019 |
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