Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
Conferences > BRAIN > 2020 > BTu2C > BTu2C.2

High-Speed Computer-Generated Holography Using Convolutional Neural Networks

M. Hossein Eybposh, Nicholas W. Caira, Praneeth Chakravarthula, Mathew Atisa, and Nicolas C. Pégard

Not Accessible

Your library or personal account may give you access

Abstract

We introduce a computer-generated holography algorithm based on deep learning with unsupervised training. Our method generates high fidelity holograms in a few milliseconds and outperforms alternate methods that require many iterations and longer computation.

© 2020 The Author(s)

PDF Article
More Like This
Computer-Generated Holography Using Point Cloud Processing Neural Networks

M. Hossein Eybposh, Changjia Cai, Diptodip Deb, Miguel A. B. Schott, Longtian Ye, Gert-Jan Both, Srinivas C. Turaga, Jose Rodriguez-Romaguera, and Nicolas C. Pégard
DW5A.4 3D Image Acquisition and Display: Technology, Perception and Applications (3D) 2023

Enhanced Two-photon Absorption with Deep Learning-based Computer Generated Holography

M. Hossein Eybposh, Nicholas W. Caira, Matthew Atisa, Praneeth Chakravarthula, and Nicolas C. Pégard
FTu2B.2 Frontiers in Optics (FiO) 2020

Convolutional Neural Networks Applied to Inline Particle Holography

Marcus Hedlund, Caroline Holmstrom, Elliot Harenby Deak, Robert Olsson, Mikael Sjodahl, and Johan Ohman
JW2A.15 3D Image Acquisition and Display: Technology, Perception and Applications (3D) 2020

View More...
Select as filters
Select Topics Cancel
Top
       
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.
Privacy | Terms of Use