Paper Abstract and Keywords |
Presentation |
2019-03-13 16:25
Improving the robusteness of neural networks to adversarial examples by reducing color depth of training inage data Shuntaro Miyazato, Toshihiko Yamasaki, Kiyoharu Aizawa (UTokyo) EMM2018-109 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In this research, we propose a method to train a neural network that is robust to adversarial examples to image classification.
First, we show that the accuracy of adversarial example can be improved while keeping the accuracy of data which is not adversarial example by dropping RGB value information of the training image.
In addition, we suggest that the robustness improves further by determining the quantization level so that the loss function is maximized just before back propagation of the neural network.
Finally, we report the ensemble of the model trained with quantization accomplished the same performance as the model adversarial trained, if they can reject indeterminate examples. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
deep learning / adversarial example / / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 118, no. 494, EMM2018-109, pp. 95-100, March 2019. |
Paper # |
EMM2018-109 |
Date of Issue |
2019-03-06 (EMM) |
ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
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EMM2018-109 |
Conference Information |
Committee |
EMM |
Conference Date |
2019-03-13 - 2019-03-14 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
TBD |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Image and Sound Quality, Metrics for Perception and Recognition, Human Auditory and Visual System, etc. |
Paper Information |
Registration To |
EMM |
Conference Code |
2019-03-EMM |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Improving the robusteness of neural networks to adversarial examples by reducing color depth of training inage data |
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deep learning |
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adversarial example |
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1st Author's Name |
Shuntaro Miyazato |
1st Author's Affiliation |
The University of Tokyo (UTokyo) |
2nd Author's Name |
Toshihiko Yamasaki |
2nd Author's Affiliation |
The University of Tokyo (UTokyo) |
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Kiyoharu Aizawa |
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The University of Tokyo (UTokyo) |
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Speaker |
Author-1 |
Date Time |
2019-03-13 16:25:00 |
Presentation Time |
25 minutes |
Registration for |
EMM |
Paper # |
EMM2018-109 |
Volume (vol) |
vol.118 |
Number (no) |
no.494 |
Page |
pp.95-100 |
#Pages |
6 |
Date of Issue |
2019-03-06 (EMM) |
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