VinayTeki/Semantic_Segmentation
KERAS: Multimodal Deep Learning for Semantic Segmentation (RGB, NIR Streams) - multiple architectures
This project helps forestry researchers and environmental scientists automate the detailed mapping of forest scenes. By taking in pairs of standard RGB images and Near-Infrared (NIR) images of the same area, it produces a segmented map that precisely outlines different elements within the forest. This enables detailed analysis of vegetation, land cover, and other features.
No commits in the last 6 months.
Use this if you need to automatically identify and classify objects or regions within forest imagery by combining visual and infrared data.
Not ideal if you are working with single-modality images (only RGB or only NIR) or require real-time processing without GPU access.
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11
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4
Language
Python
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Last pushed
Jun 19, 2017
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