| | --- |
| | license: cc-by-4.0 |
| | task_categories: |
| | - image-segmentation |
| | - image-to-image |
| | language: |
| | - en |
| | tags: |
| | - geology |
| | pretty_name: Geophysical Waveform Inversion Dataset |
| | size_categories: |
| | - 100K<n<1M |
| | --- |
| | |
| | I parsed the [full openFWI dataset](https://smileunc.github.io/projects/openfwi/datasets) as part of [this kaggle competition](https://www.kaggle.com/competitions/waveform-inversion/overview) - hopefully people can make use of this :) |
| |
|
| | If you use OpenFWI Datasets in your work, please cite... |
| | ``` |
| | @inproceedings{NEURIPS2022_27d3ef26, |
| | author = {Deng, Chengyuan and Feng, Shihang and Wang, Hanchen and Zhang, Xitong and Jin, Peng and Feng, Yinan and Zeng, Qili and Chen, Yinpeng and Lin, Youzuo}, |
| | booktitle = {Advances in Neural Information Processing Systems}, |
| | editor = {S. Koyejo and S. Mohamed and A. Agarwal and D. Belgrave and K. Cho and A. Oh}, |
| | pages = {6007--6020}, |
| | publisher = {Curran Associates, Inc.}, |
| | title = {OpenFWI: Large-scale Multi-structural Benchmark Datasets for Full Waveform Inversion}, |
| | url = {https://proceedings.neurips.cc/paper_files/paper/2022/file/27d3ef263c7cb8d542c4f9815a49b69b-Paper-Datasets_and_Benchmarks.pdf}, |
| | volume = {35}, |
| | year = {2022} |
| | } |
| | ``` |
