Frontiers of intelligent document analysis and recognition： review and prospects-Reference-Cited by-同舟云学术

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Frontiers of intelligent document analysis and recognition： review and prospects

Published:2023 Issue:8 Volume:28 Page:2223-2252
ISSN:1006-8961
Container-title:Journal of Image and Graphics
language:en
Short-container-title:

Author:

Chenglin Liu, ,Lianwen Jin,Xiang Bai,Xiaohui Li,Fei Yin

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

Reference109 articles.

1. Aberdam A，Litman R，Tsiper S，Anschel O，Slossberg R，Mazor S，Manmatha R and Perona P. 2021. Sequence-to-sequence contrastive learning for text recognition//Proceedings of 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Nashville，USA:IEEE:15297-15307 ［DOI:10.1109/CVPR46437. 2021.01505］

2. Almazán J，Gordo A，Fornés A and Valveny E. 2014. Word spotting and recognition with embedded attributes. IEEE Transactions on Pattern Analysis and Machine Intelligence，36（12）:2552-2566［DOI:10.1109/TPAMI.2014.2339814］

3. Álvaro F，Sánchez J A and Benedí J M. 2014. Recognition of on-line handwritten mathematical expressions using 2D stochastic contextfree grammars and hidden Markov models. Pattern Recognition Letters，35:58-67［DOI:10.1016/j.patrec.2012.09.023］

4. Álvaro F，Sánchez J A and Benedí J M. 2016. An integrated grammarbased approach for mathematical expression recognition. Pattern Recognition，51:135-147［DOI:10.1016/j.patcog.2015.09.013］

5. Ao X，Zhang X Y and Liu C L. 2022. Cross-modal prototype learning for zero-shot handwritten character recognition. Pattern Recognition， 131:#108859［DOI:10.1016/j.patcog.2022.108859］

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