Spectrally encoded single-pixel machine vision using diffractive networks-Reference-Cited by-同舟云学术

Spectrally encoded single-pixel machine vision using diffractive networks

Published:2021-03-26 Issue:13 Volume:7 Page:
ISSN:2375-2548
Container-title:Science Advances
language:en
Short-container-title:Sci. Adv.

Author:

Li Jingxi¹²³^ORCID,Mengu Deniz¹²³^ORCID,Yardimci Nezih T.¹³^ORCID,Luo Yi¹²³^ORCID,Li Xurong¹³,Veli Muhammed¹²³,Rivenson Yair¹²³^ORCID,Jarrahi Mona¹³^ORCID,Ozcan Aydogan¹²³^ORCID

Affiliation:

1. Electrical and Computer Engineering Department, University of California, Los Angeles, CA 90095, USA.

2. Bioengineering Department, University of California, Los Angeles, CA 90095, USA.

3. California NanoSystems Institute (CNSI), University of California, Los Angeles, CA 90095, USA.

Abstract

Diffractive networks encode the spatial information of objects into power spectrum to classify images with a single-pixel detector.

Funder

Burroughs Wellcome Fund

University of California, Los Angeles

Wellcome

Fujikura Foundation

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

Reference58 articles.

1. Negative Refraction Makes a Perfect Lens

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