HSG-AIML/IGARSS2023_EfficientDeepLearningEO
Course materials for the IGARSS 2023 Tutorial "Efficient Deep Learning for Earth Observation"
These materials help researchers and practitioners working with satellite imagery and other geospatial data to build better and more efficient machine learning models. You'll learn how to combine different data sources, train models for multiple tasks simultaneously, and leverage unlabeled data to improve your results. This is ideal for Earth observation scientists, geospatial analysts, and remote sensing engineers.
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Use this if you are a researcher or practitioner in Earth observation looking to apply or improve deep learning models for tasks like land cover mapping, environmental monitoring, or urban planning.
Not ideal if you are looking for a plug-and-play software tool, as this resource provides educational content and code examples for building your own models.
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Jupyter Notebook
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BSD-3-Clause
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Last pushed
Jul 16, 2023
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