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## CPICANN Datasets
This repository contains the data sets described in the CPICANN paper, available at [GitHub](https://github.com/WPEM/CPICANN).
CPICANN is evaluated on four distinguished datasets, denoted as D1, D2, D3, and D4, with the following characteristics:
- **D1**: 0% background ratio and Gaussian noise (σ=0.25) (v chosen in paper)
- **D2**: 3% background ratio and Gaussian noise (σ=0.25)
- **D3**: 0% background ratio and Gaussian noise (σ=1)
- **D4**: 0% background ratio and Gaussian noise (σ=3)
Contribution and suggestions are always welcome. You can also contact the authors for research collaboration.
## 📚 Citation & License
**Commercial use is strictly prohibited.**
All access will be logged.
If you use this dataset in your research, please cite **all** the following works:
```bibtex
@article{zhang2024crystallographic,
title={Crystallographic phase identifier of a convolutional self-attention neural network (CPICANN) on powder diffraction patterns},
author={Zhang, Shouyang and Cao, Bin and Su, Tianhao and Wu, Yue and Feng, Zhenjie and Xiong, Jie and Zhang, Tong-Yi},
journal={IUCrJ},
volume={11},
number={Pt 4},
pages={634},
year={2024}
}
@inproceedings{binsimxrd,
title={SimXRD-4M: Big Simulated X-ray Diffraction Data and Crystal Symmetry Classification Benchmark},
author={Bin, CAO and Liu, Yang and Zheng, Zinan and Tan, Ruifeng and Li, Jia and Zhang, Tong-yi},
booktitle={The Thirteenth International Conference on Learning Representations}
}
``` |