https://github.com/mingtaoguo/cnn-for-chinese-calligraphy-styles-classification
A convolution neural network with SE block and haar wavelet block for Chinese calligraphy styles classification by TensorFlow.(Paper: A novel CNN structure for fine-grained classification of Chinesecalligraphy styles)
https://github.com/mingtaoguo/cnn-for-chinese-calligraphy-styles-classification
cnn-classification haarwavelet squeeze-and-excitation tensorflow tensorflow-models
Last synced: 4 months ago
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A convolution neural network with SE block and haar wavelet block for Chinese calligraphy styles classification by TensorFlow.(Paper: A novel CNN structure for fine-grained classification of Chinesecalligraphy styles)
- Host: GitHub
- URL: https://github.com/mingtaoguo/cnn-for-chinese-calligraphy-styles-classification
- Owner: MingtaoGuo
- Created: 2018-05-05T02:51:42.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2019-06-12T13:23:23.000Z (almost 6 years ago)
- Last Synced: 2025-01-31T03:01:52.334Z (4 months ago)
- Topics: cnn-classification, haarwavelet, squeeze-and-excitation, tensorflow, tensorflow-models
- Language: Python
- Homepage:
- Size: 9.67 MB
- Stars: 41
- Watchers: 2
- Forks: 4
- Open Issues: 2
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Metadata Files:
- Readme: README.md
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README
# CNN-for-Chinese-Calligraphy-Styles-classification
This code mainly solves the problem of style classification of Chinese calligraphy.The paper has published: [A novel CNN structure for fine-grained classification of Chinesecalligraphy styles](https://rdcu.be/bxS19)
Introduce
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There are four famous styles in standard font that is ou, yan, liu, zhao.

Methods
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We use Squeeze-and-Excitation block and haar-wavelet block to improve the performance of our network.### The method of Squeeze-and-Excitation block:

### The method of haar-wavelet block:

### The architecture of our model:
