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Awesome GitHub RepositoriesGeospatial Model Architectures
Neural network architectures designed to process multi-dimensional geospatial data, including time series and 4D atmosphere data.
Distinct from 3D Detection Model Support: Existing candidates focus on 3D detection or simple time-series forecasting, not the broader geospatial data dimensions (2D to 4D).
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Awesome Geospatial Model Architectures GitHub Repositories
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- torchgeo/torchgeo
torchgeo/torchgeo
4,077Auf GitHub ansehenTorchGeo is a PyTorch library designed for deep learning on geospatial data, providing a framework for building and training neural networks for tasks such as semantic segmentation, object detection, and change detection. It serves as a comprehensive pipeline for remote sensing, featuring specialized dataset loaders and multispectral image preprocessing tools. The library is distinguished by a dedicated remote sensing model zoo and extensive support for transfer learning, allowing users to integrate pre-trained weights optimized for specific satellite sensors. It also includes support for sel
Implements diverse model architectures to process time series, 2D images, 3D change detection, and 4D atmosphere data.
Pythoncomputer-visiondatasetsdeep-learning
