Space Displacement Localization Neural Networks to locate origin points of handwritten text lines in historical documents
Author:
Affiliation:
1. A2iA SAS, Paris, France, INSA-Lyon, LIRIS, UMR5205, F-69621
2. A2iA SAS, Paris, France
3. Université de Lyon, CNRS, France, INSA-Lyon, LIRIS, UMR5205, F-69621
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/2809544.2809546
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3. Text line segmentation in handwritten documents using Mumford–Shah model
4. Scalable Object Detection Using Deep Neural Networks
Cited by 3 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. Instance Segmentation of Handwritten Text on Historical Document Images Using Deep Learning Approaches;4th International Conference on Artificial Intelligence and Applied Mathematics in Engineering;2023
2. Segmentation of text lines using multi-scale CNN from warped printed and handwritten document images;International Journal on Document Analysis and Recognition (IJDAR);2021-05-21
3. Fully convolutional network with dilated convolutions for handwritten text line segmentation;International Journal on Document Analysis and Recognition (IJDAR);2018-05-30
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