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geodl 0.3.0

• Support for three model architectures: UNet, UNet with MobileNetv2 encoder, and UNet3+
• UNet with MobileNetv2 encoder is no longer limited to three input predictor variables
• Assessment and prediction functions now expect a nn_module object as opposed to a luz fitted object
• Dynamically generate chips during training process as opposed to saving them to disk beforehand (still experimental)
• Ignore outer rows and columns of cells when calculating loss or assessment metrics if desired
• Use R torch to calculate several different land surface parameters (LSPs) from a digital terrain model: slope, hillshade, aspect, northwardness, eastwardness, transformed solar radiation aspect index (TRASP), site exposure index (SEI), topographic position index (TPI), and surface curvatures (mean, profile, and planform)
• Calculate three-band terrain visualization raster grid from a DTM using torch or terra
• New specialized model for extracting geomorphic features from digital terrain models (DTMs)
• New function to count the number of trainable parameters in a model
• Fixed issue with chip generation pipeline that caused some chips with NA cells to be written
• Updated atrous spatial pyramid pooling (ASPP) module to align with the version used within DeepLabv3+

geodl 0.2.0

• Initial CRAN submission.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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