An encoder-decoder based generation model for online handwritten mathematical expressions-Reference-Cited by-同舟云学术

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An encoder-decoder based generation model for online handwritten mathematical expressions

Published:2023 Issue:8 Volume:28 Page:2356-2369
ISSN:1006-8961
Container-title:Journal of Image and Graphics
language:en
Short-container-title:

Author:

Chen Yang, ,Jun Du,Mobai Xue,Jianshu Zhang

Publisher

Aerospace Information Research Institute, Chinese Academy of Sciences

Subject

Artificial Intelligence,Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Human-Computer Interaction

Reference23 articles.

1. Bian X H，Qin B，Xin X Z，Li J W，Su X F and Wang Y F. 2022.Handwritten mathematical expression recognition via attention aggregation based bi-directional mutual learning. Proceedings of the AAAI Conference on Artificial Intelligence，36（1）:113-121［DOI:10.1609/aaai.v36i1.19885］

2. Bishop C M. 1994. Mixture density networks［EB/OL］.［2022-09-01］.https://publications.aston.ac.uk/id/eprint/373/1/NCRG_94_004.pdf

3. Cho K，Van Merriënboer B，Gulcehre C，Bahdanau D，Bougares F，Schwenk H and Bengio Y. 2014. Learning phrase representations using RNN encoder-decoder for statistical machine translation［EB/OL］.［2022-09-01］. https://arxiv.org/pdf/1406.1078.pdf

4. Deng Y T，Kanervisto A，Ling J and Rush A M. 2017. Image-to-markup generation with coarse-to-fine attention［EB/OL］.［2022-09-01］.https://arxiv.org/pdf/1609.04938.pdf

5. Graves A. 2014. Generating sequences with recurrent neural networks［EB/OL］.［2022-09-01］. https://arxiv.org/pdf/1308.0850.pdf

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