Machine learning based technique towards smart laser fabrication of CGH-Reference-Cited by-同舟云学术

Machine learning based technique towards smart laser fabrication of CGH

Published:2020-04 Issue: Volume:227 Page:111314
ISSN:0167-9317
Container-title:Microelectronic Engineering
language:en
Short-container-title:Microelectronic Engineering

Author:

Anastasiou Aggeliki,Zacharaki Evangelia I.,Alexandropoulos Dimitris,Moustakas Konstantinos,Vainos Nikolaos A.

Funder

HELLAS-CH

MIS

Operational Programme “Competitiveness, Entrepreneurship and Innovation”

NSRF

European Regional Development Fund

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Surfaces, Coatings and Films,Condensed Matter Physics,Atomic and Molecular Physics, and Optics,Electronic, Optical and Magnetic Materials

Reference37 articles.

1. Label-Free Detection of Global Morphology Changes in Confluent Cell Layers Utilizing Quantitative Phase Imaging with Digital Holographic Microscopy;Kemper,2019

2. 3D Imaging in Microfluidics: New Holographic Methods and Devices;Bianco,2019

3. Securing multiple information using wavelet transform and Yang-Gu mixture amplitude-phase retrieval algorithm;Abuturab;Opt. Lasers Eng.,2019

4. 3D Image Encryption Based on Computer-Generated Hologram in the Fractional Fourier Domain;Piao,2020

5. Optical testing with computer generated holograms: comprehensive error analysis;Zhao;Opt. Manuf. Test. X,2013

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Predictive visualization of fiber laser cutting topography via deep learning with image inpainting;Journal of Laser Applications;2023-06-29

2. Laser fabrication and evaluation of holographic intrinsic physical unclonable functions;Scientific Reports;2022-02-21

3. Modelling of fibre laser cutting via deep learning;Optics Express;2021-10-21