Binarization Free Layout Analysis for Arabic Historical Documents Using Fully Convolutional Networks-Reference-Cited by-同舟云学术

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Binarization Free Layout Analysis for Arabic Historical Documents Using Fully Convolutional Networks

Published:2018-03 Issue: Volume: Page:
ISSN:
Container-title:2018 IEEE 2nd International Workshop on Arabic and Derived Script Analysis and Recognition (ASAR)
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Author:

Barakat Berat Kurar,El-Sana Jihad

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8465566/8480094/08480333.pdf?arnumber=8480333

Cited by 15 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. CNN-based Methods for Offline Arabic Handwriting Recognition: A Review;Neural Processing Letters;2024-03-19

2. A One-Shot Learning Approach to Document Layout Segmentation of Ancient Arabic Manuscripts;2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV);2024-01-03

3. A detailed exploration of Document Image Layout Retention techniques;2023 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS);2023-11-03

4. Pixel-Level Segmentation of Handwritten and Printed Texts in Document Images with Deep Learning;2023 16th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI);2023-10-28

5. Text line and word detection and recognition of historical Arabic manuscripts;2023-05-05

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