Aadit3003/u-nets-implementation
Implemented the U-Net architecture proposed by Ronneberger et. al, and used it for water body detection in a dataset of 2841 images from the Sentinel-2 satellite.
This project helps identify water bodies within satellite imagery. It takes Sentinel-2 satellite images as input and produces corresponding mask images where water is highlighted. This is useful for environmental scientists, urban planners, or remote sensing analysts who need to quickly map and monitor aquatic features.
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Use this if you need to automatically detect and outline water bodies in satellite images, for tasks like environmental monitoring or land-use analysis.
Not ideal if your primary goal is to segment highly complex or varied features beyond water bodies, or if you require extremely high precision for critical infrastructure planning.
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Sep 09, 2021
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