A Study on Defense Against Adversarial Examples and Unauthorized Access for Convolutional Neural Networks

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学術機関リポジトリデータベース（IRDB）（機関リポジトリ）

A Study on Defense Against Adversarial Examples and Unauthorized Access for Convolutional Neural Networks

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Material Type: 博士論文
Title: A Study on Defense Against Adversarial Examples and Unauthorized Access for Convolutional Neural Networks
Author/Editor: エープリル, ピョンマウンマウン
April, Pyone Maung Maung
Author Heading: エープリル, ピョンマウンマウン
April, Pyone Maung Maung
Alternative Title: 畳み込みニューラルネットワークのための敵対的サンプルと不正アクセスに対する防御法に関する研究
Pages: 1-119
Degree grantor/type: 東京都立大学
Date Granted: 2022-03-25
Dissertation Number: 甲第1135号
Degree Type: 博士（情報科学）
Text Language Code: eng
NDLC: UT51
Target Audience: 一般
Format (IMT): application/pdf
Source: april pyone_maung maung_fulltext.pdf （fulltext）
https://tokyo-metro-u.repo.nii.ac.jp/record/9680/files/april%20pyone_maung%20maung_fulltext.pdf
Access Restrictions: インターネット公開
Data Provider (Database): 国立情報学研究所 : 学術機関リポジトリデータベース（IRDB）（機関リポジトリ）
https://irdb.nii.ac.jp
Original Data Provider (Database): 東京都立大学 : みやこ鳥