fmenat/multiviewRS-models
List of deep learning models proposed for remote sensing (RS) multi-view data
This project compiles various deep learning models designed to analyze multiple types of satellite imagery and remote sensing data together. It helps remote sensing professionals, geoscientists, and environmental analysts fuse different data sources (like optical, radar, or LiDAR) to create more accurate and comprehensive maps, classifications, and environmental insights.
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Use this if you need to combine data from different remote sensing sensors to get a more complete picture of an area, for tasks such as land cover mapping, change detection, or environmental monitoring.
Not ideal if you are only working with a single type of remote sensing data or if you need general-purpose deep learning models not specifically tailored for multi-view fusion in remote sensing.
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Jun 12, 2025
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