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Seg&Struct: The Interplay Between Part Segmentation and Structure Inference for 3D Shape Parsing
We propose Seg&Struct, a supervised learning framework leveraging the interplay between part segmentation and structure inference and demonstrating their synergy in an integrated framework.
Predicting resonant properties of plasmonic structures by deep learning
Deep learning can be used to extract meaningful results from images.
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