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Found 5 papers, 0 papers with code
Deep learning based workflow for accelerated industrial X-ray Computed Tomography
Furthermore, traditional workflows based on using analytic reconstruction algorithms require a large number of projections for accurate characterization - leading to longer measurement times and hindering the adoption of XCT for in-line inspections.
YOLO2U-Net: Detection-Guided 3D Instance Segmentation for Microscopy
Microscopy imaging techniques are instrumental for characterization and analysis of biological structures.
Model-based Reconstruction for Enhanced X-ray CT of Tri-structural Isotropic (TRISO) Particles
Tri-Structural Isotropic (TRISO) fuel particles are a key component of next generation nuclear fuels.
PABO: Pseudo Agent-Based Multi-Objective Bayesian Hyperparameter Optimization for Efficient Neural Accelerator Design
The ever increasing computational cost of Deep Neural Networks (DNN) and the demand for energy efficient hardware for DNN acceleration has made accuracy and hardware cost co-optimization for DNNs tremendously important, especially for edge devices.
X-Ray CT Reconstruction of Additively Manufactured Parts using 2.5D Deep Learning MBIR
We then train a 2. 5D deep convolutional neural network [4], deemed 2. 5D Deep Learning MBIR (2. 5D DL-MBIR), on these pairs of noisy and high-quality 3D volumes to learn a fast, non-linear mapping function.
