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Gum-Net: Unsupervised Geometric Matching for Fast and Accurate 3D Subtomogram Image Alignment and Averaging
We propose a Geometric unsupervised matching Network (Gum-Net) for finding the geometric correspondence between two images with application to 3D subtomogram alignment and averaging. Subtomogram alignment is the most important task in cryo-electron tomography (cryo-ET), a revolutionary 3D imaging te...
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| Publicat a: | Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit |
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| Autors principals: | , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
2020
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7955792/ https://ncbi.nlm.nih.gov/pubmed/33716478 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/cvpr42600.2020.00413 |
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