Learning-based Denoising Algorithm for the Reconstructed Image using Electromagnetic Emanations from the Display Device

Taesik Nam, Dong Hoon Choi, Eui Bum Lee, Jong Gwan Yook

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes a learning-based denoising algorithm that improves the signal-to-noise ratio (SNR) of the information signal emitted from the display device. The information signal is easily degraded by noise and interference on the channel and has various SNR. In this situation, an algorithm that enhances the model's robustness is required to improve the degraded information signal into a learning-based denoising model. Therefore, this paper proposes a normalization method to enhance the robustness of the model.

Original languageEnglish
Title of host publication2022 IEEE International Symposium on Electromagnetic Compatibility and Signal/Power Integrity, EMCSI 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages268-271
Number of pages4
ISBN (Electronic)9781665409292
DOIs
Publication statusPublished - 2022
Event2022 IEEE International Symposium on Electromagnetic Compatibility and Signal/Power Integrity, EMCSI 2022 - Spokane, United States
Duration: 2022 Aug 12022 Aug 5

Publication series

Name2022 IEEE International Symposium on Electromagnetic Compatibility and Signal/Power Integrity, EMCSI 2022

Conference

Conference2022 IEEE International Symposium on Electromagnetic Compatibility and Signal/Power Integrity, EMCSI 2022
Country/TerritoryUnited States
CitySpokane
Period22/8/122/8/5

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Signal Processing
  • Energy Engineering and Power Technology
  • Safety, Risk, Reliability and Quality

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