Convolutional Neural Networks (CNNs) for Earth Systems Science

Process of conovolving a filter with an image

Convolutional Neural Networks (CNNs) are a powerful class of deep learning models widely applied in Earth science for image analysis, classification, and regression problems. Leveraging the Keras framework in python, CNNs can efficiently process and extract spatial features from 2D and 3D remote sensing, model output, and other Earth Systems Science (ESS) data types.

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SSEC Unidata Server Has Been Shut Down!

The NSF Unidata server hosted at the Space Science and Engineering Center (SSEC) at the University of Wisconsin, Madison (unidata3.ssec.wisc.edu) has been permanently decommissioned.

Those who used the services provided by unidata3.ssec.wisc.edu should switch to the following alternate servers:

Service If you used Switch to
McIDAS ADDE adde.ssec.wisc.edu adde.ucar.edu
IDD/LDM Upstream idd.ssec.wisc.edu idd.unidata.ucar.edu
HTTP access to IDD Data atm.ucar.edu

Please reach out to us at support@unidata.ucar.edu if you have any questions!

Why is the Keras 3 Release a Big Deal for the Deep Learning Community?

Chart depicting use of different machine learning frameworks

The Keras package is an open-source library that provides a Python interface for deep learning. Keras is intended to be a user-friendly, modular, and extensible way to enable fast experimentation with deep neural networks. With Keras version 3, the package provides APIs for using three backends: TensorFlow, Jax, and PyTorch.

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SSEC Unidata Server Shutting Down in April 2024

The NSF Unidata server hosted at the Space Science and Engineering Center (SSEC) at the University of Wisconsin, Madison (unidata3.ssec.wisc.edu) will be permanently decomissioned on April 26, 2024.

Those using services provided by unidata3.ssec.wisc.edu can switch to using the servers described in this article.

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Shutdown of Two Special-Purpose THREDDS Data Servers

NSF Unidata will be shutting down two existing special-purpose THREDDS Data Servers on April 15, 2024. Please read the full article for details.

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News and information from the Unidata Program Center
News@Unidata
News and information from the Unidata Program Center

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