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Rob Fergus
Rob Fergus
Research Scientist, DeepMind. Professor of Computer Science, New York University
Bestätigte E-Mail-Adresse bei cs.nyu.edu - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Visualizing and understanding convolutional networks
MD Zeiler, R Fergus
European conference on computer vision, 818-833, 2014
162582014
Intriguing properties of neural networks
C Szegedy, W Zaremba, I Sutskever, J Bruna, D Erhan, I Goodfellow, ...
arXiv preprint arXiv:1312.6199, 2013
109972013
Intriguing properties of neural networks
C Szegedy, W Zaremba, I Sutskever, J Bruna, D Erhan, I Goodfellow, ...
arXiv preprint arXiv:1312.6199, 2013
109972013
Learning spatiotemporal features with 3d convolutional networks
D Tran, L Bourdev, R Fergus, L Torresani, M Paluri
Proceedings of the IEEE international conference on computer vision, 4489-4497, 2015
70452015
Overfeat: Integrated recognition, localization and detection using convolutional networks
P Sermanet, D Eigen, X Zhang, M Mathieu, R Fergus, Y LeCun
arXiv preprint arXiv:1312.6229, 2013
55492013
Learning generative visual models from few training examples: An incremental bayesian approach tested on 101 object categories
L Fei-Fei, R Fergus, P Perona
2004 conference on computer vision and pattern recognition workshop, 178-178, 2004
45212004
Indoor segmentation and support inference from rgbd images
N Silberman, D Hoiem, P Kohli, R Fergus
European conference on computer vision, 746-760, 2012
44212012
Depth map prediction from a single image using a multi-scale deep network
D Eigen, C Puhrsch, R Fergus
Advances in neural information processing systems 27, 2014
31312014
Object class recognition by unsupervised scale-invariant learning
R Fergus, P Perona, A Zisserman
2003 IEEE Computer Society Conference on Computer Vision and Pattern …, 2003
29962003
Spectral hashing
Y Weiss, A Torralba, R Fergus
Advances in neural information processing systems 21, 2008
29612008
Regularization of neural networks using dropconnect
L Wan, M Zeiler, S Zhang, Y Le Cun, R Fergus
International conference on machine learning, 1058-1066, 2013
27092013
Predicting depth, surface normals and semantic labels with a common multi-scale convolutional architecture
D Eigen, R Fergus
Proceedings of the IEEE international conference on computer vision, 2650-2658, 2015
25772015
End-to-end memory networks
S Sukhbaatar, J Weston, R Fergus
Advances in neural information processing systems 28, 2015
25642015
One-shot learning of object categories
L Fei-Fei, R Fergus, P Perona
IEEE transactions on pattern analysis and machine intelligence 28 (4), 594-611, 2006
24762006
Removing camera shake from a single photograph
R Fergus, B Singh, A Hertzmann, ST Roweis, WT Freeman
Acm Siggraph 2006 Papers, 787-794, 2006
24472006
Deep generative image models using a laplacian pyramid of adversarial networks
EL Denton, S Chintala, R Fergus
Advances in neural information processing systems 28, 2015
23672015
80 million tiny images: A large data set for nonparametric object and scene recognition
A Torralba, R Fergus, WT Freeman
IEEE transactions on pattern analysis and machine intelligence 30 (11), 1958 …, 2008
20712008
Image and depth from a conventional camera with a coded aperture
A Levin, R Fergus, F Durand, WT Freeman
ACM transactions on graphics (TOG) 26 (3), 70-es, 2007
18482007
Deconvolutional networks
MD Zeiler, D Krishnan, GW Taylor, R Fergus
2010 IEEE Computer Society Conference on computer vision and pattern …, 2010
17942010
Exploiting linear structure within convolutional networks for efficient evaluation
EL Denton, W Zaremba, J Bruna, Y LeCun, R Fergus
Advances in neural information processing systems 27, 2014
16042014
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