airg/unet-efficientnet-b7-ltfl-mmgab-100ep-2window-ftw

U-Net generally conforming to the current FTW baseline 3-class model settings, trained on the Fields of the World full dataset, using both time points (Window A, Window B) for 100 epochs. The model is the same as the current FTW PRUE variant with EfficientNet-b7 backbone, but was trained using a locally-weighted Tversky Focal Loss rather Logcoshdice, and using global min-max across band normalization using the 1st and 99th percentile image values. See here for code and configuration.

Performance metrics on the validation split (calculated across samples drawn from countries listed below):

	pixel level				object level
iou	precision	recall	f1	precision	recall	f1
0.816	0.914	0.884	0.899	0.488	0.364	0.417

Data included in validation set:

• Austria
• Belgium
• Cambodia
• Corsica
• Croatia
• Denmark
• Estonia
• Finland
• France
• Germany
• Latvia
• Lithuania
• Luxembourg
• Netherlands
• Slovakia
• Slovenia
• South Africa
• Spain
• Sweden
• Vietnam