Segmenting Handwritten Math Symbols Using AdaBoost and Multi-scale Shape Context Features-Reference-Cited by-同舟云学术

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Segmenting Handwritten Math Symbols Using AdaBoost and Multi-scale Shape Context Features

Published:2013-08 Issue: Volume: Page:
ISSN:
Container-title:2013 12th International Conference on Document Analysis and Recognition
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Author:

Hu Lei,Zanibbi Richard

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/6627713/6628563/06628800.pdf?arnumber=6628800

Cited by 17 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. Multimodal Dependence Attention and Large-Scale Data Based Offline Handwritten Formula Recognition;Journal of Computer Science and Technology;2024-05

2. Recent trends in mathematical expressions recognition: An LDA-based analysis;Expert Systems with Applications;2023-03

3. A dive in white and grey shades of ML and non-ML literature: a multivocal analysis of mathematical expressions;Artificial Intelligence Review;2022-12-06

4. Synthetic Data Generation and Shuffled Multi-Round Training Based Offline Handwritten Mathematical Expression Recognition;Journal of Computer Science and Technology;2022-11-30

5. Image Segmentation Techniques: Statistical, Comprehensive, Semi-Automated Analysis and an Application Perspective Analysis of Mathematical Expressions;Archives of Computational Methods in Engineering;2022-08-22

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