Advancing Multilingual Handwritten Numeral Recognition With Attention-Driven Transfer Learning-Reference-Cited by-同舟云学术

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Advancing Multilingual Handwritten Numeral Recognition With Attention-Driven Transfer Learning

Published:2024 Issue: Volume:12 Page:41381-41395
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Fateh Amirreza¹^ORCID,Birgani Reza Tahmasbi²,Fateh Mansoor²^ORCID,Abolghasemi Vahid³^ORCID

Affiliation:

1. School of Computer Engineering, Iran University of Science and Technology (IUST), Tehran, Iran

2. Faculty of Computer Engineering, Shahrood University of Technology, Shahrood, Iran

3. School of Computer Science and Electronic Engineering, University of Essex, Colchester, U.K.

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10474004.pdf?arnumber=10474004

Reference46 articles.

1. Deep Learning Model for Recognition of Handwritten Devanagari Numerals With Low Computational Complexity and Space Requirements

2. Handwritten Gujarati Numerals Classification Based on Deep Convolution Neural Networks Using Transfer Learning Scenarios

3. Two Decades of Bengali Handwritten Digit Recognition: A Survey

4. Enhancing optical character recognition: Efficient techniques for document layout analysis and text line detection

5. A comparison of deep neural network models for cluster cancer patients through somatic point mutations

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