Fully automated extraction of the fringe skeletons in dynamic electronic speckle pattern interferometry using a U-Net convolutional neural network
Author:
Affiliation:
1. Tianjin University, School of Electronic and Information Engineering, Tianjin
2. Dalian University of Technology, State Key Laboratory of Structural Analysis for Industrial Equipmen
Publisher
SPIE-Intl Soc Optical Eng
Subject
General Engineering,Atomic and Molecular Physics, and Optics
Reference30 articles.
1. Vibration mode shapes visualization in industrial environment by real-time time-averaged phase-stepped electronic speckle pattern interferometry at 10.6 μ m and shearography at 532 nm
2. Real-time one-point out-of-plane displacement measurement system using electronic speckle pattern interferometry
3. Use of specklegrams background terms for speckle photography combined with phase-shifting electronic speckle pattern interferometry
4. Phase extraction from a single fringe pattern based on guidance of an extreme map
5. Performance evaluation of partial differential equation models in electronic speckle pattern interferometry and the δ-mollification phase map method
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1. Deep Learning in the Phase Extraction of Electronic Speckle Pattern Interferometry;Electronics;2024-01-19
2. Channel transformer U-Net: an automatic and effective skeleton extraction network for electronic speckle pattern interferometry;Applied Optics;2023-01-03
3. Parameter Fitting-Based Fast Imaging of Axisymmetric Flame Temperature Field Using Wavelength-Modulated Lateral Shearing Interferometry;IEEE Transactions on Instrumentation and Measurement;2023
4. Batch skeleton extraction from ESPI fringe patterns using pix2pix conditional generative adversarial network;Optical Review;2022-03-10
5. Phase Extraction of Electronic Speckle Interference Fringe Image based on Convolutional Neural Network;2021 7th International Conference on Computing and Artificial Intelligence;2021-04-23
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