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Resting state fMRI functional connectivity-based classification using a
  convolutional neural network architecture

Resting state fMRI functional connectivity-based classification using a convolutional neural network architecture

20 July 2017
R. Meszlényi
Krisztián Búza
Zoltán Vidnyánszky
ArXiv (abs)PDFHTML

Papers citing "Resting state fMRI functional connectivity-based classification using a convolutional neural network architecture"

10 / 10 papers shown
Title
Deriving reproducible biomarkers from multi-site resting-state data: An
  Autism-based example
Deriving reproducible biomarkers from multi-site resting-state data: An Autism-based example
Alexandre Abraham
M. Milham
A. di Martino
Cameron R. Craddock
Dimitris Samaras
Bertrand Thirion
Gaël Varoquaux
68
575
0
18 Nov 2016
Learning rotation invariant convolutional filters for texture
  classification
Learning rotation invariant convolutional filters for texture classification
Diego Marcos
Michele Volpi
D. Tuia
74
148
0
22 Apr 2016
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
2.1K
150,433
0
22 Dec 2014
Machine Learning for Neuroimaging with Scikit-Learn
Machine Learning for Neuroimaging with Scikit-Learn
Alexandre Abraham
Fabian Pedregosa
Michael Eickenberg
Philippe Gervais
A. Mueller
Jean Kossaifi
Alexandre Gramfort
Bertrand Thirion
Gaël Varoquaux
AI4CE
80
1,827
0
12 Dec 2014
Scale-Invariant Convolutional Neural Networks
Scale-Invariant Convolutional Neural Networks
Yichong Xu
Tianjun Xiao
Jiaxing Zhang
Kuiyuan Yang
Zheng Zhang
117
138
0
24 Nov 2014
Going Deeper with Convolutions
Going Deeper with Convolutions
Christian Szegedy
Wei Liu
Yangqing Jia
P. Sermanet
Scott E. Reed
Dragomir Anguelov
D. Erhan
Vincent Vanhoucke
Andrew Rabinovich
496
43,717
0
17 Sep 2014
On the Number of Linear Regions of Deep Neural Networks
On the Number of Linear Regions of Deep Neural Networks
Guido Montúfar
Razvan Pascanu
Kyunghyun Cho
Yoshua Bengio
96
1,256
0
08 Feb 2014
Deep learning for neuroimaging: a validation study
Deep learning for neuroimaging: a validation study
Sergey Plis
R. Devon Hjelm
Ruslan Salakhutdinov
Vince D. Calhoun
AI4CE
136
574
0
20 Dec 2013
Dropout Training as Adaptive Regularization
Dropout Training as Adaptive Regularization
Stefan Wager
Sida I. Wang
Percy Liang
133
600
0
04 Jul 2013
Representation Learning: A Review and New Perspectives
Representation Learning: A Review and New Perspectives
Yoshua Bengio
Aaron Courville
Pascal Vincent
OODSSL
288
12,467
0
24 Jun 2012
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