[HTML][HTML] Deep learning in optical metrology: a review

C Zuo, J Qian, S Feng, W Yin, Y Li, P Fan… - Light: Science & …, 2022 - nature.com
With the advances in scientific foundations and technological implementations, optical
metrology has become versatile problem-solving backbones in manufacturing, fundamental …

On the use of deep learning for phase recovery

K Wang, L Song, C Wang, Z Ren, G Zhao… - Light: Science & …, 2024 - nature.com
Phase recovery (PR) refers to calculating the phase of the light field from its intensity
measurements. As exemplified from quantitative phase imaging and coherent diffraction …

Quantitative phase imaging based on holography: trends and new perspectives

Z Huang, L Cao - Light: Science & Applications, 2024 - nature.com
Abstract In 1948, Dennis Gabor proposed the concept of holography, providing a pioneering
solution to a quantitative description of the optical wavefront. After 75 years of development …

[HTML][HTML] Deep holography

G Situ - Light: Advanced Manufacturing, 2022 - light-am.com
With the explosive growth of mathematical optimization and computing hardware, deep
neural networks (DNN) have become tremendously powerful tools to solve many …

Deep learning spatial phase unwrapping: a comparative review

K Wang, Q Kemao, J Di, J Zhao - Advanced Photonics Nexus, 2022 - spiedigitallibrary.org
Phase unwrapping is an indispensable step for many optical imaging and metrology
techniques. The rapid development of deep learning has brought ideas to phase …

PhaseNet 2.0: Phase unwrapping of noisy data based on deep learning approach

GE Spoorthi, RKSS Gorthi… - IEEE transactions on image …, 2020 - ieeexplore.ieee.org
Phase unwrapping is an ill-posed classical problem in many practical applications of
significance such as 3D profiling through fringe projection, synthetic aperture radar and …

Deep learning-based branch-cut method for InSAR two-dimensional phase unwrapping

L Zhou, H Yu, Y Lan, M Xing - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Two-dimensional (2-D) phase unwrapping (PU) is a critical processing step for many
synthetic aperture radar (SAR) interferometry (InSAR) applications. As is well known, the …

Artificial intelligence in interferometric synthetic aperture radar phase unwrapping: A review

L Zhou, H Yu, Y Lan - IEEE Geoscience and Remote Sensing …, 2021 - ieeexplore.ieee.org
Interferometric synthetic aperture radar (InSAR) is a radar technique widely used in geodesy
and remote sensing applications, eg, topography reconstruction and subsidence estimation …

Deep learning for the detection and phase unwrapping of mining-induced deformation in large-scale interferograms

Z Wu, T Wang, Y Wang, R Wang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
This article proposes deep convolutional neural networks to detect and map localized, rapid
subsidence caused by mining activities using time-series Sentinel-1 synthetic aperture radar …

Single-shot fringe projection profilometry based on deep learning and computer graphics

F Wang, C Wang, Q Guan - Optics Express, 2021 - opg.optica.org
Multiple works have applied deep learning to fringe projection profilometry (FPP) in recent
years. However, to obtain a large amount of data from actual systems for training is still a …