Exploring 3D Denoising with Machine Learning and Vision Transformers (ViT) | |
3D denoising in machine learning refers to the process of removing noise from 3d denosing machine learning vit data, such as medical imaging or 3D scans, to enhance the quality and accuracy of the information. Vision Transformers have recently been applied to this task, utilizing their attention mechanisms to better capture spatial dependencies across 3D structures. This method improves noise reduction while preserving fine details in complex 3D data. ![]() | |
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