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Extended results of "Electro-Magnetic Side-Channel Attack Through Learned Denoising and Classification" paper

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This repository presents more examples for the experimental part of Electro-Magnetic Side-Channel Attack Through Learned Denoising and Classification, F. Lemarchand, F. Montreuil, C. Marlin, E. Nogues and M. Pelcat.

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Denoising results

99 representative samples are shown for Mask-RCNN, auto-encoder and BM3D. Samples are displayed using the following format: left sample is the reference one (clean), middle is the noisy, right is the denoised.

Jump to Mask-RCNN samples

Jump to Auto-Encoder samples

Jump to BM3D samples

Denoising using Mask-RCNN

Denoising using auto-encoder

Denoising using BM3D

Licensing

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

The data is free to use until you propagate the licence and you cite our paper using the following format:

BIBTEX OF THE PAPER TO INCLUDE.

Contact

Florian Lemarchand : A@B.fr, A=florian.lemarchand and B = insa-rennes

About

Extended results of "Electro-Magnetic Side-Channel Attack Through Learned Denoising and Classification" paper

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