Feature Extraction and Dimensionality Reduction Models for Printed Numerals Recognition-Reference-Cited by-同舟云学术

Feature Extraction and Dimensionality Reduction Models for Printed Numerals Recognition

Published:2022-03-23 Issue: Volume: Page:
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Container-title:2022 9th International Conference on Computing for Sustainable Global Development (INDIACom)
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Author:

Rani Lekha¹,Sahoo Ashok Kumar²,Sarangi Pradeepta Kumar¹,Yadav Chandra Shekhar³,Rath Bishnu Prasad⁴

Affiliation:

1. Chitkara University Institute of Engineering & Technology, Chitkara University,Department of CSE,Punjab,India

2. Graphic Era Hill University,Department of CSE,Dehradun,India

3. Noida Institute of Engineering and Technology,Department of CSE,Greater Noida,U.P,India

4. Cognizant Technology Solutions Ltd.,Computer Science

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9763090/9763103/09763290.pdf?arnumber=9763290

Reference20 articles.

1. Recognition of offline handwritten numerals using an ensemble of MLPs combined by Adaboost

2. A comparative analysis of image transformations for handwritten Odia numeral recognition

3. A System for Oriya Handwritten Numeral Recognition for Indian Postal Automation;mahato;International Journal of Applied Science &Technology Research,2011

4. Handwritten Numeral Recognition of Six Popular Indian Scripts

5. An HMM Based Recognition Scheme for Handwritten Oriya Numerals

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