WAP

This repository contains the source code for WAP introduced in the following papers:<br>

• VGG: Watch, attend and parse: An end-to-end neural network based approach to handwritten mathematical expression recognition<br>
• DenseNet: Multi-Scale Attention with Dense Encoder for Handwritten Mathematical Expression Recognition<br>

Here, VGG contains the code that employs VGG architecture as the watcher, DenseNet contains the code that employs DenseNet as the watcher.<br>

Requirements

• Install cuda-8.0 cudnn-v7
• Install Theano.0.10.0 with libgpuarray

Citation

If you find WAP useful in your research, please consider citing:

@article{zhang2017watch,
  title={Watch, attend and parse: An end-to-end neural network based approach to handwritten mathematical expression recognition},
  author={Zhang, Jianshu and Du, Jun and Zhang, Shiliang and Liu, Dan and Hu, Yulong and Hu, Jinshui and Wei, Si and Dai, Lirong},
  journal={Pattern Recognition},
  volume={71},
  pages={196--206},
  year={2017},
  publisher={Elsevier}
}

@inproceedings{zhang2018multi,
  title={Multi-scale attention with dense encoder for handwritten mathematical expression recognition},
  author={Zhang, Jianshu and Du, Jun and Dai, Lirong},
  booktitle={International Conference on Pattern Recognition},
  pages={2245--2250},
  year={2018}
}

Contact

xysszjs at mail.ustc.edu.cn<br> West campus of University of Science and Technology of China<br> Any discussions, suggestions and questions are welcome!