Document Image Binarization with Fully Convolutional Neural Networks-Reference-Cited by-同舟云学术

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Document Image Binarization with Fully Convolutional Neural Networks

Published:2017-11 Issue: Volume: Page:
ISSN:
Container-title:2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR)
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Author:

Tensmeyer Chris,Martinez Tony

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8269349/8269930/08269956.pdf?arnumber=8269956

Cited by 106 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. Image quality determination of palm leaf heritage documents using integrated discrete cosine transform features with vision transformer;International Journal on Document Analysis and Recognition (IJDAR);2024-07-17

2. An Efficient Transformer–CNN Network for Document Image Binarization;Electronics;2024-06-07

3. Generate, transform, and clean: the role of GANs and transformers in palm leaf manuscript generation and enhancement;International Journal on Document Analysis and Recognition (IJDAR);2024-05-20

4. A Review of Document Binarization: Main Techniques, New Challenges, and Trends;Electronics;2024-04-07

5. Binarization of Malayalam Palm Leaf Images using VGG Net and Integrated Otsu;2024 IEEE 9th International Conference for Convergence in Technology (I2CT);2024-04-05

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