Stars
The Galileo family of pretrained remote sensing models
Easy fine-tuning of Geo foundation models
Pytorch package with lots of tools for geospatial deep learning
A high-performance Python-based I/O system for large (and small) deep learning problems, with strong support for PyTorch.
Documents describing the governance of the Spack project.
Official repo for "Foundation Models for Remote Sensing and Earth Observation: A Survey"
A toolkit that enables building damage assessments from remotely sensed imagery.
A comprehesive survey about foundation models for weather and cliamte data understanding.
Automatic conversion of standard Python packages to Spack package recipes.
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
Transfer Learning for Global Crop Type Mapping
This repository serves as a guide on how to reproduce the work done on my submission for the Artificial Intelligence for Earth Observation integrated course(VI).
The user-friendly command line shell.
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
The official repository for the EuroCrops dataset.
Images used to run Gitlab pipelines in the cloud
An extremely fast Python linter and code formatter, written in Rust.
Code for Neural Plasticity-Inspired Foundation Model for Observing the Earth Crossing Modalities
Pretrain, finetune ANY AI model of ANY size on multiple GPUs, TPUs with zero code changes.
Machine learning metrics for distributed, scalable PyTorch applications.
Segmentation models with pretrained backbones. PyTorch.
Lightning-UQ-Box: Uncertainty Quantification for Neural Networks with PyTorch and Lightning
🛰️ List of satellite image training datasets with annotations for computer vision and deep learning
A technical report on convolution arithmetic in the context of deep learning