Synergizing SVM Classifier with Hybrid CNN Architecture for Handwritten Recognition-Reference-Cited by-同舟云学术

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Synergizing SVM Classifier with Hybrid CNN Architecture for Handwritten Recognition

Published:2024-03-05 Issue: Volume: Page:1-5
ISSN:
Container-title:2024 International Conference on Emerging Smart Computing and Informatics (ESCI)
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Author:

Sujay V.¹,Lakshmi B. Seetha²,Venkatesan T.³,Ram S Sakthiya⁴,Sangeetha E.⁵,Satheeshkumar S.⁵

Affiliation:

1. Krishna University College of Engineering and Technology,Department of Computer Science and Engineering,Machilipatnam,Andhra Pradesh,India

2. Sri Shanmugha College of Engineering and Technology,Department of Artificial Intelligence and Data Science,Namakkal,Tamil Nadu,India

3. R.M.D. Engineering College,Department of Mathematics,Thiruvallur,Tamil Nadu,India

4. Bannari Amman Institute of Technology,Department of ECE,Erode,Tamil Nadu,India

5. Paavai Engineering College (Autonomous),Department of ECE,Namakkal,Tamil Nadu,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10497186/10497189/10497404.pdf?arnumber=10497404

Reference16 articles.

1. Integrating Writing Dynamics in CNN for Online Children Handwriting Recognition

2. Distilling Content from Style for Handwritten Word Recognition

3. Handwritten Character and Digit Recognition with Deep Convolutional Neural Networks: A Comparative Study

4. A Semantic Segmentation-based Method for Handwritten Japanese Text Recognition

5. Handwriting recognition in Tibetan based on active learning strategy

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