Text Line Segmentation in Historical Document Images Using an Adaptive U-Net Architecture-Reference-Cited by-同舟云学术

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Text Line Segmentation in Historical Document Images Using an Adaptive U-Net Architecture

Published:2019-09 Issue: Volume: Page:
ISSN:
Container-title:2019 International Conference on Document Analysis and Recognition (ICDAR)
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Author:

Mechi Olfa,Mehri Maroua,Ingold Rolf,Essoukri Ben Amara Najoua

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8961318/8977948/08978147.pdf?arnumber=8978147

Cited by 43 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. GAN-based text line segmentation method for challenging handwritten documents;International Journal on Document Analysis and Recognition (IJDAR);2024-07-21

2. Approximate ground truth generation for semantic labeling of historical documents with minimal human effort;International Journal on Document Analysis and Recognition (IJDAR);2024-06-12

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

4. Historical Text Line Segmentation Using Deep Learning Algorithms: Mask-RCNN against U-Net Networks;Journal of Imaging;2024-03-05

5. Digitizing History: Transitioning Historical Paper Documents to Digital Content for Information Retrieval and Mining—A Comprehensive Survey;IEEE Transactions on Computational Social Systems;2024

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