Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Toward Training a Deep Neural Network to Optimize Lens Designs

Not Accessible

Your library or personal account may give you access


A deep neural network (DNN) is trained in an unsupervised manner, using RMS spot size, to output optimized lens designs from provided specifications.

© 2018 The Author(s)

PDF Article
More Like This
Training deep neural networks for the inverse design of nanophotonic structures

Dianjing Liu, Yixuan Tan, Erfan Khoram, and Zongfu Yu
JF2F.4 CLEO: Applications and Technology (CLEO_AT) 2019

On the Use of Deep Learning for Lens Design

Geoffroi Côté, Jean-François Lalonde, and Simon Thibault
120781A International Optical Design Conference (IODC) 2021

Towards to deep neural network application with limited training data: synthesis of melanoma’s diffuse reflectance spectral images

Katrina Bolochko, Dmitrijs Bliznuks, Dilshat Uteshev, Ilze Lihacova, Alexey Lihachev, Yuriy Chizhov, and Andrey Bondarenko
11074_66 European Conference on Biomedical Optics (ECBO) 2019


You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
Login to access Optica Member Subscription

Poster Presentation

Media 1: PDF (1790 KB)     
Select as filters

Select Topics Cancel
© Copyright 2023 | Optica Publishing Group. All Rights Reserved