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Automatic recognition for complex scenes from aerial images and other sensor data (e.g. LiDAR) has become an active topic in the remote sensing community. In this paper, we proposed a novel framework that utilizes higher-order CRFs (HCRFs) to capture the spatial contextual information for the RGB aerial images along with their co-registered LiDAR data (DSMs). Our proposed HCRFs framework exploits...
The increasing availability of very-high-resolution (VHR) aerial optical images as well as coregistered Li- DAR data opens great opportunities for improving objectlevel dense semantic labeling of airborne remote sensing imagery. As a result, efficient and effective multisensor fusion techniques are needed to fully exploit these complementary data modalities. Recent researches demonstrated how to process...
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