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A Deep Learning-based Global and Segmentation-based Semantic Feature Fusion Approach for Indoor Scene Classification

By Ricardo Pereira and others
This work proposes a novel approach that uses a semantic segmentation mask to obtain a 2D spatial layout of the segmentation-categories across the scene, designated by segmentation-based semantic features (SSFs). These features represent, per segmentation-category, the pixel count, as well as the 2D average position and respective standard deviation values.... Show more
January 31, 2024
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A Deep Learning-based Global and Segmentation-based Semantic Feature Fusion Approach for Indoor Scene Classification
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