Abstract: Accurate semantic segmentation of high-resolution remote sensing imagery is essential for applications ranging from urban planning to environmental monitoring. However, this task remains ...
Abstract: The fusion of optical, hyperspectral, and synthetic aperture radar (SAR) images is essential for semantic segmentation in remote sensing, enabling more comprehensive land cover ...
This sample app demonstrates how to create technical documents for a codebase using AI. More specifically, it uses the agent framework offered by Semantic Kernel to ochestrate multiple agents to ...
Task: Classify every pixel of a synthetic desert offroad image into one of 10 semantic classes: Background, Trees, Lush Bushes, Dry Grass, Dry Bushes, Ground Clutter, Logs, Rocks, Landscape, and Sky.
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