LSPARCOM: Deep unfolded super-resolution microscopy

Gili Dardikman-Yoffe; Yonina C. Eldar

doi:https://doi.org/10.1364/3D.2020.JW5A.5

LSPARCOM: Deep unfolded super-resolution microscopy

Gili Dardikman-Yoffe, Yonina C. Eldar

Department of Computer Science and Applied Mathematics

Weizmann Institute of Science

Research output: Contribution to journal › Conference article › peer-review

Abstract

We present a novel high-density single molecule localization microscopy technique, which combines a classical compressed sensing method with deep learning through an algorithm unfolding procedure, yielding a compact and robust neural network considering domain knowledge.

Original language	English
Article number	JW5A.5
Number of pages	2
Journal	Optics InfoBase Conference Papers
DOIs	https://doi.org/10.1364/3D.2020.JW5A.5
State	Published - 2020
Event	Computational Optical Sensing and Imaging, COSI 2020 - Part of Imaging and Applied Optics Congress 2020 - Virtual, Online, United States Duration: 22 Jun 2020 → 26 Jun 2020

All Science Journal Classification (ASJC) codes

Electronic, Optical and Magnetic Materials
Mechanics of Materials

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https://doi.org/10.1364/3D.2020.JW5A.5

Cite this

@article{e739a065aa984f50baa78d002614f645,

title = "LSPARCOM: Deep unfolded super-resolution microscopy",

abstract = "We present a novel high-density single molecule localization microscopy technique, which combines a classical compressed sensing method with deep learning through an algorithm unfolding procedure, yielding a compact and robust neural network considering domain knowledge.",

author = "Gili Dardikman-Yoffe and Eldar, {Yonina C.}",

note = "Publisher Copyright: {\textcopyright} 2020 The Author(s).; Computational Optical Sensing and Imaging, COSI 2020 - Part of Imaging and Applied Optics Congress 2020 ; Conference date: 22-06-2020 Through 26-06-2020",

year = "2020",

doi = "https://doi.org/10.1364/3D.2020.JW5A.5",

language = "الإنجليزيّة",

journal = "Optics InfoBase Conference Papers",

issn = "2162-2701",

}

TY - JOUR

T1 - LSPARCOM

T2 - Computational Optical Sensing and Imaging, COSI 2020 - Part of Imaging and Applied Optics Congress 2020

AU - Dardikman-Yoffe, Gili

AU - Eldar, Yonina C.

PY - 2020

Y1 - 2020

N2 - We present a novel high-density single molecule localization microscopy technique, which combines a classical compressed sensing method with deep learning through an algorithm unfolding procedure, yielding a compact and robust neural network considering domain knowledge.

AB - We present a novel high-density single molecule localization microscopy technique, which combines a classical compressed sensing method with deep learning through an algorithm unfolding procedure, yielding a compact and robust neural network considering domain knowledge.

UR - http://www.scopus.com/inward/record.url?scp=85118616138&partnerID=8YFLogxK

U2 - https://doi.org/10.1364/3D.2020.JW5A.5

DO - https://doi.org/10.1364/3D.2020.JW5A.5

M3 - مقالة من مؤنمر

SN - 2162-2701

JO - Optics InfoBase Conference Papers

JF - Optics InfoBase Conference Papers

M1 - JW5A.5

Y2 - 22 June 2020 through 26 June 2020

ER -

LSPARCOM: Deep unfolded super-resolution microscopy

Abstract

All Science Journal Classification (ASJC) codes

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