Skip to content

Latest commit

 

History

History
332 lines (313 loc) · 11.9 KB

README.md

File metadata and controls

332 lines (313 loc) · 11.9 KB

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.

Contact and License Terms

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