A Combination of Supervised Encoder-Decoder Neural Networks with Time-multiplexed Coded Apertures for Gamma and Lensless Imaging

Yossef Danan, Amir Shemer, Eliezer Danan, Ariel Schwarz

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In order to improve sensitivity, signal to noise ratio and overcoming inverse filtering limitations in gamma and lensless imaging reconstruction, a method of combining supervised encoder-decoder neural networks with variable coded aperture is used.

Original languageEnglish
Title of host publicationApplied Industrial Spectroscopy in Proceedings Optica Sensing Congress 2023, AIS, FTS, HISE, Sensors, ES 2023
PublisherOptical Society of America
ISBN (Electronic)9781957171241
DOIs
StatePublished - 2023
Externally publishedYes
EventApplied Industrial Spectroscopy in Proceedings Optica Sensing Congress 2023, AIS, FTS, HISE, Sensors, ES 2023 - Part of Optical Sensors and Sensing Congress 2023 - Munich, Germany
Duration: 30 Jul 20233 Aug 2023

Publication series

NameApplied Industrial Spectroscopy in Proceedings Optica Sensing Congress 2023, AIS, FTS, HISE, Sensors, ES 2023

Conference

ConferenceApplied Industrial Spectroscopy in Proceedings Optica Sensing Congress 2023, AIS, FTS, HISE, Sensors, ES 2023 - Part of Optical Sensors and Sensing Congress 2023
Country/TerritoryGermany
CityMunich
Period30/07/233/08/23

Bibliographical note

Publisher Copyright:
© 2023 The Author (s).

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