Using seven contiguous CT slices as input improves super-resolved image quality and defect detection for additively manufactured parts compared with single-slice 2D networks, at near-2D memory cost.
Real-time single image and video super- resolution using an efficient sub-pixel convolutional neural network
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2.5D Super-Resolution Approaches for X-ray Computed Tomography-based Inspection of Additively Manufactured Parts
Using seven contiguous CT slices as input improves super-resolved image quality and defect detection for additively manufactured parts compared with single-slice 2D networks, at near-2D memory cost.