HENet: Forcing a Network to Think More for Font Recognition-Reference-Cited by-同舟云学术

HENet: Forcing a Network to Think More for Font Recognition

Published:2021-11-26 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 3rd International Conference on Advanced Information Science and System
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Author:

Chen Jingchao¹,Mu Shiyi¹,Xu Shugong¹,Ding Youdong¹

Affiliation:

1. Shanghai University, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3503047.3503055

Reference16 articles.

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2. Robert Cooperman. 1997. Producing good font attribute determination using error-prone information. In Document Recognition IV. Robert Cooperman. 1997. Producing good font attribute determination using error-prone information. In Document Recognition IV.

3. Font-ProtoNet: Prototypical Network based Font Identification of Document Images in Low Data Regime

4. Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2016. Deep residual learning for image recognition. In CVPR. Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2016. Deep residual learning for image recognition. In CVPR.

5. Shuangping Huang , Zhuoyao Zhong , Lianwen Jin , Shuye Zhang , and Haobin Wang . 2018. DropRegion training of inception font network for high-performance Chinese font recognition. Pattern Recognition (May 2018 ). Shuangping Huang, Zhuoyao Zhong, Lianwen Jin, Shuye Zhang, and Haobin Wang. 2018. DropRegion training of inception font network for high-performance Chinese font recognition. Pattern Recognition (May 2018).

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