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Found 5 papers, 0 papers with code
Automated Multiscale 3D Feature Learning for Vessels Segmentation in Thorax CT Images
Following their idea of feature learning instead of hand-crafted filters, we have extended the method to learn 3D features.
Reference Setup for Quantitative Comparison of Segmentation Techniques for Short Glass Fiber CT Data
We suggest both the metrics and this data set as a reference for studying the performance of different algorithms.
Instance Segmentation of Fibers from Low Resolution CT Scans via 3D Deep Embedding Learning
We propose a novel approach for automatic extraction (instance segmentation) of fibers from low resolution 3D X-ray computed tomography scans of short glass fiber reinforced polymers.
Fully Convolutional Deep Network Architectures for Automatic Short Glass Fiber Semantic Segmentation from CT scans
We present the first attempt to perform short glass fiber semantic segmentation from X-ray computed tomography volumetric datasets at medium (3. 9 {\mu}m isotropic) and low (8. 3 {\mu}m isotropic) resolution using deep learning architectures.
A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems
However, on new and challenging types of models our findings disagree and suggest that polyhedral methods and integer programming solvers are competitive in terms of runtime and solution quality over a large range of model types.
