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Bayesian Image Quality Transfer with CNNs: Exploring Uncertainty in dMRI
  Super-Resolution
v1v2 (latest)

Bayesian Image Quality Transfer with CNNs: Exploring Uncertainty in dMRI Super-Resolution

1 May 2017
Ryutaro Tanno
Daniel E. Worrall
Aurobrata Ghosh
Enrico Kaden
S. Sotiropoulos
A. Criminisi
Daniel C. Alexander
    UQCVDiffMMedImSupR
ArXiv (abs)PDFHTML

Papers citing "Bayesian Image Quality Transfer with CNNs: Exploring Uncertainty in dMRI Super-Resolution"

5 / 55 papers shown
Real-Time Single Image and Video Super-Resolution Using an Efficient
  Sub-Pixel Convolutional Neural Network
Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network
Wenzhe Shi
Jose Caballero
Ferenc Huszár
J. Totz
Andrew P. Aitken
Rob Bishop
Daniel Rueckert
Zehan Wang
SupR
1.3K
5,732
0
16 Sep 2016
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
Justin Johnson
Alexandre Alahi
Li Fei-Fei
SupR
685
11,097
0
27 Mar 2016
Variational Dropout and the Local Reparameterization Trick
Variational Dropout and the Local Reparameterization TrickNeural Information Processing Systems (NeurIPS), 2015
Diederik P. Kingma
Tim Salimans
Max Welling
BDL
603
1,620
0
08 Jun 2015
Image Super-Resolution Using Deep Convolutional Networks
Image Super-Resolution Using Deep Convolutional NetworksIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2014
Chao Dong
Chen Change Loy
Kaiming He
Xiaoou Tang
SupR
744
8,925
0
31 Dec 2014
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic OptimizationInternational Conference on Learning Representations (ICLR), 2014
Diederik P. Kingma
Jimmy Ba
ODL
4.8K
162,118
0
22 Dec 2014
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