[HTML][HTML] Deep learning in optical metrology: a review
With the advances in scientific foundations and technological implementations, optical
metrology has become versatile problem-solving backbones in manufacturing, fundamental …
metrology has become versatile problem-solving backbones in manufacturing, fundamental …
On the use of deep learning for phase recovery
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 …
measurements. As exemplified from quantitative phase imaging and coherent diffraction …
[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 …
neural networks (DNN) have become tremendously powerful tools to solve many …
Speeding up reconstruction of 3D tomograms in holographic flow cytometry via deep learning
Tomographic flow cytometry by digital holography is an emerging imaging modality capable
of collecting multiple views of moving and rotating cells with the aim of recovering their …
of collecting multiple views of moving and rotating cells with the aim of recovering their …
Machine learning holography for 3D particle field imaging
We propose a new learning-based approach for 3D particle field imaging using holography.
Our approach uses a U-net architecture incorporating residual connections, Swish …
Our approach uses a U-net architecture incorporating residual connections, Swish …
Digital holographic imaging and classification of microplastics using deep transfer learning
We devise an inline digital holographic imaging system equipped with a lightweight deep
learning network, termed CompNet, and develop the transfer learning for classification and …
learning network, termed CompNet, and develop the transfer learning for classification and …
Dense-U-net: dense encoder–decoder network for holographic imaging of 3D particle fields
Digital holographic imaging is able to reconstruct phase and three-dimensional (3D)
information of an object from a one-shot two-dimensional (2D) lensless hologram. A dense …
information of an object from a one-shot two-dimensional (2D) lensless hologram. A dense …
[HTML][HTML] DarkFocus: numerical autofocusing in digital in-line holographic microscopy using variance of computational dark-field gradient
We report on a novel computational technique for automatic numerical refocusing in digital
in-line holographic microscopy. It is based on the adaptive filtering of the recorded on-axis …
in-line holographic microscopy. It is based on the adaptive filtering of the recorded on-axis …
Recent advances and applications of digital holography in multiphase reactive/nonreactive flows: a review
In various multiphase flows, the characterization of particle dynamics is important in the
understanding of the interaction between particles and the surrounding flows. Digital …
understanding of the interaction between particles and the surrounding flows. Digital …
[PDF][PDF] 卷积神经网络在光学信息处理中的应用研究进展
邸江磊， 唐雎， 吴计， 王凯强， 任振波… - Laser & …, 2021 - researching.cn
摘要近年来, 深度学习技术的爆发式发展引领了机器学习的又一次浪潮. 深度神经网络具备抽象
特征的高效识别与提取能力, 强大的非线性拟合能力, 抗干扰鲁棒性及非凡的泛化能力 …
特征的高效识别与提取能力, 强大的非线性拟合能力, 抗干扰鲁棒性及非凡的泛化能力 …