Flood Extent Forecasting On Global Flood
Metriken
F1 score
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Modellname | F1 score | Paper Title | Repository |
---|---|---|---|
3DConv U-Net | 0.76 | Semantic segmentation of crop type in Africa: A novel dataset and analysis of deep learning methods | |
U-TAE | 0.77 | Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks | |
LSTM U-Net | 0.76 | Semantic segmentation of crop type in Africa: A novel dataset and analysis of deep learning methods | |
logistic regression | 0.66 | Next Day Wildfire Spread: A Machine Learning Data Set to Predict Wildfire Spreading from Remote-Sensing Data | |
MaxViT U-Net | 0.75 | MaxViT-UNet: Multi-Axis Attention for Medical Image Segmentation |
0 of 5 row(s) selected.