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Crop Type Mapping with Deep Learning using TensorFlow (#maptimeDavis)
November 10, 2020 @ 10:00 am - 12:00 pm
We will give a brief tutorial on machine learning methods in remote sensing. The focus will be on newer Deep Learning (Convolutional Neural Network) techniques, doing semantic segmentation with a UNet model. Not sure what all that means, no problem, and no installation, you’ll do it all on the cloud with Python and Tensorflow in Jupyter Notebooks and the freemium Google Colab platform.
Alex Mandel & Lily Thomas, Development Seed
- Understand how to apply Convolutional Neural Network techniques to remote sensing data
Previous experience with Python programming, Jupyter Notebooks, or classifying remotely sensed images will be helpful but is not required.
Participants should plan to have the following for the workshop:
- Participants will need a Google account (Gmail, UC Davis or other Google Login) and a web browser. We will use Google Colab to run the examples in python notebooks, try logging in with your Google Account https://colab.research.google.com
Registration is recommended but not required. Please register here.
#maptimeDavis Workshops & Studio is brought to you by DataLab’s Spatial Sciences Research & Learning Cluster and members of the UC Davis spatial community.