WAP

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

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

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

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
West campus of University of Science and Technology of China
Any discussions, suggestions and questions are welcome!