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Recent research has focused on learning 3D data through deep learning and improving geometric processing methods. Two aspects distinguish deep learning of point clouds from deep learning of images. A core aspect of the point cloud data is that it is disordered in comparison to the 2D image, so when designing the network, we need to consider how to deal with it. Reinforcement learning maximizes the expectation of cumulative rewards. The point cloud data was used for modeling and applied to the sole surface construction to achieve better results.
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