Image Reconstruction Improvement of Variable Coded Aperture Using Deep Learning Method for Gamma and Lensless Imaging Applications-Reference-Cited by-同舟云学术

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Image Reconstruction Improvement of Variable Coded Aperture Using Deep Learning Method for Gamma and Lensless Imaging Applications

Published:2023-06-26 Issue: Volume: Page:
ISSN:
Container-title:2023 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC)
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Author:

Schwarz Ariel¹,Shemer Amir¹,Danan Eliezer²,Cohen Noa E.³,Danan Yossef¹

Affiliation:

1. Azrieli College of Engineering,Department of Electrical and Electronics Engineering,Jerusalem,Israel,9103501

2. Bar-Ilan University,Faculty of Engineering,Ramat-Gan,Israel,5290002

3. School of Software Engineering and Computer Science, Azrieli College of Engineering,Jerusalem,Israel,9103501

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10231377/10231353/10232678.pdf?arnumber=10232678

Reference4 articles.

1. Gamma Radiation Imaging System via Variable and Time-Multiplexed Pinhole Arrays

2. Computational expansion of imaging from visible to IR and gamma imaging systems

3. Lensless three-dimensional integral imaging using variable and time multiplexed pinhole array

4. Light intensity and SNR improvement for high-resolution optical imaging via time multiplexed pinhole arrays

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