文献
J-GLOBAL ID:202002261325587421
整理番号:20A2782015
多様な画像破壊に対してロバストなニューラルネットワークを作る簡単な方法【JST・京大機械翻訳】
A Simple Way to Make Neural Networks Robust Against Diverse Image Corruptions
著者 (12件):
Rusak Evgenia
(University of Tuebingen, Tuebingen, Germany)
,
Rusak Evgenia
(International Max Planck Research School for Intelligent Systems, Tuebingen, Germany)
,
Schott Lukas
(University of Tuebingen, Tuebingen, Germany)
,
Schott Lukas
(International Max Planck Research School for Intelligent Systems, Tuebingen, Germany)
,
Zimmermann Roland S.
(University of Tuebingen, Tuebingen, Germany)
,
Zimmermann Roland S.
(International Max Planck Research School for Intelligent Systems, Tuebingen, Germany)
,
Bitterwolf Julian
(International Max Planck Research School for Intelligent Systems, Tuebingen, Germany)
,
Bringmann Oliver
(University of Tuebingen, Tuebingen, Germany)
,
Bethge Matthias
(University of Tuebingen, Tuebingen, Germany)
,
Bethge Matthias
(International Max Planck Research School for Intelligent Systems, Tuebingen, Germany)
,
Brendel Wieland
(University of Tuebingen, Tuebingen, Germany)
,
Brendel Wieland
(International Max Planck Research School for Intelligent Systems, Tuebingen, Germany)
資料名:
Lecture Notes in Computer Science
(Lecture Notes in Computer Science)
巻:
12348
ページ:
53-69
発行年:
2020年
JST資料番号:
H0078D
ISSN:
0302-9743
資料種別:
会議録 (C)
記事区分:
原著論文
発行国:
ドイツ (DEU)
言語:
英語 (EN)