Gender Classification from Offline Handwriting Images in Urdu Script: LeNet-5 and Alex-Net-Reference-Cited by-同舟云学术

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Gender Classification from Offline Handwriting Images in Urdu Script: LeNet-5 and Alex-Net

Published:2023-05-02 Issue: Volume: Page:
ISSN:
Container-title:2023 3rd International Conference on Applied Artificial Intelligence (ICAPAI)
language:
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Author:

Nabi Syed Tufael¹,Singh Paramjeet¹,Kumar Munish²

Affiliation:

1. GZS Campus College of Engineering and Technology, Maharaja Ranjit Singh Punjab Technical University,Department of Computer Science and Engineering,Bathinda,Punjab,India,151001

2. Maharaja Ranjit Singh Punjab Technical University,Department of Computational Sciences,Bathinda,Punjab,India,151001

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10193875/10193865/10194140.pdf?arnumber=10194140

Reference19 articles.

1. PCA-based gender classification system using hybridization of features and classification techniques

2. Gender and Handedness Prediction from Offline Handwriting Using Convolutional Neural Networks

3. Data Driven Feature Extraction for Gender Classification using Multi-Script Handwritten Texts

4. Handwriting based gender classification using COLD and hinge features;gattal;Lecture Notes in Computer Science,2020

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A convolution deep architecture for gender classification of urdu handwritten characters;Multimedia Tools and Applications;2024-01-31

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