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Found 7 papers, 2 papers with code
Generative deep learning-enabled ultra-large field-of-view lens-free imaging
Advancements in high-throughput biomedical applications necessitate real-time, large field-of-view (FOV) imaging capabilities.
Digital twin-assisted three-dimensional electrical capacitance tomography for multiphase flow imaging
Three-dimensional electrical capacitance tomography (3D-ECT) has shown promise for visualizing industrial multiphase flows.
Regularized Shallow Image Prior for Electrical Impedance Tomography
The results suggest that combining the shallow image prior and the hand-crafted regularization can achieve similar performance to the Deep Image Prior (DIP) but with less architectural dependency and complexity of the neural network.
A Learning-Based 3D EIT Image Reconstruction Method
Deep learning has been widely employed to solve the Electrical Impedance Tomography (EIT) image reconstruction problem.
Impedance-optical Dual-modal Cell Culture Imaging with Learning-based Information Fusion
While Electrical Impedance Tomography (EIT) has found many biomedicine applications, a better resolution is needed to provide quantitative analysis for tissue engineering and regenerative medicine.
MMV-Net: A Multiple Measurement Vector Network for Multi-frequency Electrical Impedance Tomography
Deep learning has been extensively applied in solving the EIT inverse problem in biomedical and industrial process imaging.
Event generator tuning using Bayesian optimization
In this article, we show that Monte Carlo event generator parameters can be accurately obtained using Bayesian optimization and minimal expert-level physics knowledge.
Data Analysis, Statistics and Probability High Energy Physics - Experiment Nuclear Experiment
