All-digital quantum ghost imaging: tutorial

C Moodley, A Forbes - JOSA B, 2023 - opg.optica.org
Quantum ghost imaging offers many advantages over classical imaging, including the ability
to probe an object with one wavelength and record the image with another, while low photon …

Silicon-Based Avalanche Photodiodes: Advancements and Applications in Medical Imaging

KA Lozovoy, RMH Douhan, VV Dirko, H Deeb… - Nanomaterials, 2023 - mdpi.com
Avalanche photodiodes have emerged as a promising technology with significant potential
for various medical applications. This article presents an overview of the advancements and …

Practical advantage of quantum machine learning in ghost imaging

T Xiao, X Zhai, X Wu, J Fan, G Zeng - Communications Physics, 2023 - nature.com
Demonstrating the practical advantage of quantum computation remains a long-standing
challenge whereas quantum machine learning becomes a promising application that can be …

Adaptive 3D descattering with a dynamic synthesis network

W Tahir, H Wang, L Tian - Light: Science & Applications, 2022 - nature.com
Deep learning has been broadly applied to imaging in scattering applications. A common
framework is to train a descattering network for image recovery by removing scattering …

Deep learning approach for denoising low-SNR correlation plenoptic images

F Scattarella, D Diacono, A Monaco, N Amoroso… - Scientific Reports, 2023 - nature.com
Abstract Correlation Plenoptic Imaging (CPI) is a novel volumetric imaging technique that
uses two sensors and the spatio-temporal correlations of light to detect both the spatial …

Super-resolved quantum ghost imaging

C Moodley, A Forbes - Scientific Reports, 2022 - nature.com
Quantum ghost imaging offers many advantages over classical imaging, including low
photon fluxes and non-degenerate object and image wavelengths for imaging light sensitive …

Deep learning early stopping for non-degenerate ghost imaging

C Moodley, B Sephton, V Rodríguez-Fajardo… - Scientific Reports, 2021 - nature.com
Quantum ghost imaging offers many advantages over classical imaging, including the ability
to probe an object with one wavelength and record the image with another (non-degenerate …

High-quality and high-diversity conditionally generative ghost imaging based on denoising diffusion probabilistic model

S Mao, Y He, H Chen, H Zheng, J Liu, Y Yuan, M Le… - Optics …, 2023 - opg.optica.org
Deep-learning (DL) methods have gained significant attention in ghost imaging (GI) as
promising approaches to attain high-quality reconstructions with limited sampling rates …

[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 …

Deep unfolding for singular value decomposition compressed ghost imaging

C Zhang, J Zhou, J Tang, F Wu, H Cheng, S Wei - Applied Physics B, 2022 - Springer
The non-negativity of the measurement matrix in the traditional compressed ghost imaging
system and iterative optimization process leads to low imaging quality and slow …