Art
J-GLOBAL ID：201602289327011796   Reference number：16A1403989

Deeper Depth Prediction with Fully Convolutional Residual Networks

完全畳込み残留ネットワークを用いたより深い深さ予測【Powered by NICT】
Author (5)：
Laina Iro

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, 
Rupprecht Christian

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, 
Belagiannis Vasileios

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, 
Tombari Federico

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, 
Navab Nassir

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Material：
IEEE Conference Proceedings  (IEEE Conf Proc)

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Volume： 2016  Issue： 3DV  Page： 239-248  Publication year： 2016 
JST Material Number： W2441A  Document type： Proceedings
Article type： 原著論文  Country of issue： United States (USA)  Language： ENGLISH (EN)
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This paper addresses the probl...
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refinement

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, 
computer architecture

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, 
*convolution

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, 
optimization

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, 
simple eye

About simple eye

, 
video recorder

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, 
resolving power

About resolving power

, 
end-to-end signaling system

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, 
modeling

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, 
image

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, 
aftertreatment

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, 
Learning

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, 
depth map

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, 
modification

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Semi thesaurus term：
Thesaurus term/Semi thesaurus term
Keywords indexed to the article.
All keywords is available on JDreamIII(charged).
On J-GLOBAL, this item will be available after more than half a year after the record posted. In addtion, medical articles require to login to MyJ-GLOBAL.
訓練データ

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アップサンプリング

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JST classification (1)：
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Graphic and image processing in general 
(JE04010I)

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畳込み

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残留

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予測

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