fmenat/DSensDp
Public repository of our research work at IEEE Access
This project helps Earth observation specialists analyze satellite imagery and other multi-sensor data more reliably. It takes raw data, even with missing sensor inputs, and produces robust classifications, such as identifying land cover types or environmental changes. This is for researchers and practitioners who work with satellite and geospatial data and need accurate insights despite data gaps.
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Use this if you are an Earth observation data scientist or researcher dealing with classification tasks where sensor data might be incomplete or occasionally missing.
Not ideal if your primary concern is not Earth observation, or if you need to process single-sensor data without any missing values.
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Jul 18, 2025
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