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Paper Abstract and Keywords
Presentation 2020-02-27 14:00
An Image Transformation Network for Privacy-Preserving Deep Neural Networks
Hiroki Ito, Yuma Kinoshita, Hitoshi Kiya (Tokyo Metro. Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) We propose an image transformation network to generate visually-protected images for privacy-preserving deep neural networks (DNNs). The transformation network inspired by adversarial examples is considered not only to generate visually-protected images but also to achieve the performance of DNNs that using plain images has. Moreover, the proposed transformation network can be public to users, so there is no need to manage secret keys. In an image classification experiment, the proposed transformation network is confirmed to protect the visual information without any performance degradation under the use of two image classification networks: ResNet and VGG.
Keyword (in Japanese) (See Japanese page) 
(in English) Adversarial example / deep neural network / privacy preserving / visual protection / / / /  
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Conference Information
Committee HI IEICE-IE IEICE-ITS MMS ME AIT  
Conference Date 2020-02-27 - 2020-02-28 
Place (in Japanese) (See Japanese page) 
Place (in English) Hokkaido Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Image Processing, etc. 
Paper Information
Registration To IEICE-IE 
Conference Code 2020-02-HI-IE-ITS-MMS-ME-AIT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) An Image Transformation Network for Privacy-Preserving Deep Neural Networks 
Sub Title (in English)  
Keyword(1) Adversarial example  
Keyword(2) deep neural network  
Keyword(3) privacy preserving  
Keyword(4) visual protection  
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1st Author's Name Hiroki Ito  
1st Author's Affiliation Tokyo Metropolitan University (Tokyo Metro. Univ.)
2nd Author's Name Yuma Kinoshita  
2nd Author's Affiliation Tokyo Metropolitan University (Tokyo Metro. Univ.)
3rd Author's Name Hitoshi Kiya  
3rd Author's Affiliation Tokyo Metropolitan University (Tokyo Metro. Univ.)
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Speaker Author-1 
Date Time 2020-02-27 14:00:00 
Presentation Time 15 minutes 
Registration for IEICE-IE 
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Volume (vol) vol.44 
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