[HTML][HTML] Deep-learning computational holography: A review

T Shimobaba, D Blinder, T Birnbaum, I Hoshi… - Frontiers in …, 2022 - frontiersin.org
Deep learning has been developing rapidly, and many holographic applications have been
investigated using deep learning. They have shown that deep learning can outperform …

Neural-network-based methods in digital and computer-generated holography: a review

PA Cheremkhin, DA Rymov, AS Svistunov… - Journal of Optical …, 2024 - opg.optica.org
Subject of study. An overview of modern neural-network-based methods for digital and
computer-generated holography is presented. Relevant works on phase and amplitude …

[PDF][PDF] Effect of bit-depth in stochastic gradient descent performance for phase-only computer-generated holography displays

A Kadis, B Wetherfield, J Sha, F Yang… - London Imaging …, 2022 - researchgate.net
SGD (Stochastic gradient descent) is an emerging technique for achieving high-fidelity
projected images in CGH (computergenerated holography) display systems. For real-world …

Учредители: Государственный оптический институт им. СИ Вавилова, Национальный исследовательский университет ИТМО, Международная …

ПА ЧЕРЁМХИН, ДА РЫМОВ, АС СВИСТУНОВ… - ОПТИЧЕСКИЙ …, 2024 - elibrary.ru
Предмет исследования. Аналитический обзор применения актуальных нейросетевых
методов для задач цифровой и компьютерной голографии, в том числе для …

High dynamic range (HDR) imaging for camera-in-the-loop computer-generated holography (CGH) using spatially varying pixel exposures

A Kadis, Y Wang, F Yang, R Mouthaan… - Practical …, 2022 - spiedigitallibrary.org
A traditional limitation of holographic displays has been their image quality. Recent
advances in computer-generated holography using a camera-in-the-loop (CITL) approach …