ClimateNet Looks to Machine Learning for Global Climate Science

Pattern recognition tasks such as classification, localization, object detection and segmentation have remained challenging problems in the weather and climate sciences. Now, a team at the Lawrence Berkeley National Laboratory is developing ClimateNet, a project that will bring the power of deep learning methods to identify important weather and climate patterns via expert-labeled, community-sourced open datasets and architectures.

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