[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 …
metrology has become versatile problem-solving backbones in manufacturing, fundamental …
Artificial intelligence-enabled quantitative phase imaging methods for life sciences
J Park, B Bai, DH Ryu, T Liu, C Lee, Y Luo, MJ Lee… - Nature …, 2023 - nature.com
Quantitative phase imaging, integrated with artificial intelligence, allows for the rapid and
label-free investigation of the physiology and pathology of biological systems. This review …
label-free investigation of the physiology and pathology of biological systems. This review …
An on-chip photonic deep neural network for image classification
F Ashtiani, AJ Geers, F Aflatouni - Nature, 2022 - nature.com
Deep neural networks with applications from computer vision to medical diagnosis,,,–are
commonly implemented using clock-based processors,,,,,,,–, in which computation speed is …
commonly implemented using clock-based processors,,,,,,,–, in which computation speed is …
Inference in artificial intelligence with deep optics and photonics
G Wetzstein, A Ozcan, S Gigan, S Fan, D Englund… - Nature, 2020 - nature.com
Artificial intelligence tasks across numerous applications require accelerators for fast and
low-power execution. Optical computing systems may be able to meet these domain-specific …
low-power execution. Optical computing systems may be able to meet these domain-specific …
[HTML][HTML] Far-field super-resolution ghost imaging with a deep neural network constraint
F Wang, C Wang, M Chen, W Gong, Y Zhang… - Light: Science & …, 2022 - nature.com
Ghost imaging (GI) facilitates image acquisition under low-light conditions by single-pixel
measurements and thus has great potential in applications in various fields ranging from …
measurements and thus has great potential in applications in various fields ranging from …
Neural holography with camera-in-the-loop training
Y Peng, S Choi, N Padmanaban… - ACM Transactions on …, 2020 - dl.acm.org
Holographic displays promise unprecedented capabilities for direct-view displays as well as
virtual and augmented reality applications. However, one of the biggest challenges for …
virtual and augmented reality applications. However, one of the biggest challenges for …
Single-pixel imaging 12 years on: a review
GM Gibson, SD Johnson, MJ Padgett - Optics express, 2020 - opg.optica.org
Modern cameras typically use an array of millions of detector pixels to capture images. By
contrast, single-pixel cameras use a sequence of mask patterns to filter the scene along with …
contrast, single-pixel cameras use a sequence of mask patterns to filter the scene along with …
[HTML][HTML] Roadmap of terahertz imaging 2021
G Valušis, A Lisauskas, H Yuan, W Knap, HG Roskos - Sensors, 2021 - mdpi.com
In this roadmap article, we have focused on the most recent advances in terahertz (THz)
imaging with particular attention paid to the optimization and miniaturization of the THz …
imaging with particular attention paid to the optimization and miniaturization of the THz …
Snapshot compressive imaging: Theory, algorithms, and applications
X Yuan, DJ Brady… - IEEE Signal Processing …, 2021 - ieeexplore.ieee.org
Capturing high-dimensional (HD) data is a long-term challenge in signal processing and
related fields. Snapshot compressive imaging (SCI) uses a 2D detector to capture HD (≥ …
related fields. Snapshot compressive imaging (SCI) uses a 2D detector to capture HD (≥ …
Deep learning techniques for inverse problems in imaging
G Ongie, A Jalal, CA Metzler… - IEEE Journal on …, 2020 - ieeexplore.ieee.org
Recent work in machine learning shows that deep neural networks can be used to solve a
wide variety of inverse problems arising in computational imaging. We explore the central …
wide variety of inverse problems arising in computational imaging. We explore the central …