long123524/TFNet
Official code: "Integrating Segment Anything Model derived boundary prior and high-level semantics for cropland extraction from high-resolution remote sensing images
This project helps agricultural analysts and environmental scientists accurately map cropland areas from satellite images. It takes high-resolution remote sensing images as input and generates precise outlines of cultivated fields, helping to monitor land use, crop growth, and environmental changes. The target users are professionals in agricultural planning, environmental monitoring, or remote sensing.
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Use this if you need to precisely identify and map individual cropland boundaries from detailed satellite imagery.
Not ideal if you require real-time analysis or are working with low-resolution aerial photography, as it's designed for high-resolution satellite data.
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Language
Python
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Last pushed
May 26, 2025
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