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3d Shape - Wiley Online Library

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Last Updated: 10 May 2022

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Double weighting convolutional neural net‐works for multi‐view 3D shape recognition

The developed bidirectional long-term memory module will help investigate the relationships between the views in detail and raise the quality of the extracted parts. Further, the new L2 norm framework can be used to determine the discrimination score of views and group views more accurately. After successful grouping and weighted fusion activities are used within and between groups to fuse attributes in order to produce group-level descriptors that better represent each group of views. Compact 3D shape descriptors for 3D object recognition are later developed by similarly important group-level descriptors for 3D object recognition.

Source link: https://onlinelibrary.wiley.com/doi/10.1049/cvi2.12107

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions