Papers Read on AI

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June 30, 2022  

TorchGeo: deep learning with geospatial data

June 30, 2022

Remotely sensed geospatial data are critical for applications including precision agriculture, urban planning, disaster monitoring and response, and climate change research, among others. Deep learning methods are particularly promising for modeling many remote sensing tasks given the success of deep neural networks in similar computer vision tasks and the sheer volume of remotely sensed imagery available.

2021: A. Stewart, Caleb Robinson, Isaac A. Corley, Anthony Ortiz, J. Ferres, Arindam Banerjee