Wafer-Map-Active-Learning

This is the code for our paper:
Active Learning of Convolutional Neural Network for Cost-effective Wafer Map Pattern Classification, by Jaewoong Shim, Seokho Kang, and Sungzoon Cho, IEEE Transactions on Semiconductor Manufacturing, 2020.

How to run it

1. get WM-811K dataset: https://www.kaggle.com/qingyi/wm811k-wafer-map
2. make the preprocessed data with read_data.py
3. you can start an experiment using run_topk_div_val.py

Citation

@article{shim2020active,
  title={Active Learning of Convolutional Neural Network for Cost-Effective Wafer Map Pattern Classification},
  author={Shim, Jaewoong and Kang, Seokho and Cho, Sungzoon},
  journal={IEEE Transactions on Semiconductor Manufacturing},
  volume={33},
  number={2},
  pages={258--266},
  year={2020},
  publisher={IEEE}
}