Tropical Cyclone Wind Estimation Model
ml-model resnet18 regression supervised |
This is a PyTorch model trained on the Tropical Cyclone Wind Estimation Competition dataset with v0.1 of the TorchGeo package. The model is a resnet18 model pretrained on ImageNet then trained with a MSE loss. The data were randomly split 80/20 by storm ID and an early stop was used based on performance.
Model ID | model-cyclone-wind-estimation-torchgeo-v1 |
DOI | 10.5281/zenodo.5773331browse DOI |
Creator | Microsoft AI for Good Research Lab (Caleb Robinson) |
Contact | caleb.robinson@microsoft.com |
License | MIT |
Applicable Temporal Extent | 2000-01-01 / present |
Publications
Stewart, A., Robinson, C. and Corley, I., 2021. TorchGeo: deep learning with geospatial data. arXiv preprint arXiv:2111.08872, [online] (11). Available at: https://arxiv.org/abs/2111.08872 [Date Accessed].
Citation
Caleb Robinson. (2021). Tropical Cyclone Wind Estimation model (2.0). Zenodo. https://doi.org/10.5281/zenodo.5773331.
Inferencing Image Example
docker pull docker.io/radiantearth/cyclone-model-torchgeo:1
Assets and Links
| Inference Runtime | Model inferencing runtime |
| Checkpoint | Final model checkpoint |
| Training Data | Training Data Source, Training Data Labels |
| Inferencing Image | docker.io/radiantearth/cyclone-model-torchgeo:1 |
| Related MLHub Dataset | Tropical Cyclone Wind Estimation Competition Dataset |
CONNECT
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