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Adapting Deep Network Features to Capture Psychological Representations

Adapting Deep Network Features to Capture Psychological Representations

6 August 2016
Joshua C. Peterson
Joshua T. Abbott
Thomas Griffiths
ArXivPDFHTML

Papers citing "Adapting Deep Network Features to Capture Psychological Representations"

6 / 6 papers shown
Title
Delving Deep into Rectifiers: Surpassing Human-Level Performance on
  ImageNet Classification
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
VLM
171
18,534
0
06 Feb 2015
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
301
43,511
0
17 Sep 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAtt
MDE
928
99,991
0
04 Sep 2014
Pixels to Voxels: Modeling Visual Representation in the Human Brain
Pixels to Voxels: Modeling Visual Representation in the Human Brain
Pulkit Agrawal
D. Stansbury
Jitendra Malik
J. Gallant
40
103
0
18 Jul 2014
Caffe: Convolutional Architecture for Fast Feature Embedding
Caffe: Convolutional Architecture for Fast Feature Embedding
Yangqing Jia
Evan Shelhamer
Jeff Donahue
Sergey Karayev
Jonathan Long
Ross B. Girshick
S. Guadarrama
Trevor Darrell
VLM
BDL
3DV
190
14,703
0
20 Jun 2014
Intriguing properties of neural networks
Intriguing properties of neural networks
Christian Szegedy
Wojciech Zaremba
Ilya Sutskever
Joan Bruna
D. Erhan
Ian Goodfellow
Rob Fergus
AAML
166
14,831
1
21 Dec 2013
1