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Convolutional networks are powerful visual models that yield hierarchies of features.
Backpropagation applied to hand-written zip code recognition
Y. LeCun, B. Boser, J. Denker, D. Henderson, R. E. Howard, W. Hubbard, and L. D. Jackel · 1989
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Multi-digit recognition using a space displacement neural network
O. Matan, C. J. Burges, Y. LeCun, and J. S. Denker · 1991
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Postal address block location using a convolutional locator network
R. Wolf and J. C. Platt · 1994
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The gaussian scale-space paradigm and the multiscale local jet
L. Florack, B. T. H. Romeny, M. Viergever, and J. Koenderink · 1996
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Efficient backprop
Y. A. LeCun, L. Bottou, G. B. Orr, and K.-R. Müller · 1998
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Toward automatic phenotyping of developing embryos from videos
F. Ning, D. Delhomme, Y. LeCun, F. Piano, L. Bottou, and P. E. Barbano · 2005
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Superparsing: scalable nonparametric image parsing with superpixels
J. Tighe and S. Lazebnik · 2010
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The PASCAL Visual Object Classes Challenge 2011 (VOC2011) Results
M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman · 2011
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Semantic contours from inverse detectors
B. Hariharan, P. Arbelaez, L. Bourdev, S. Maji, and J. Malik · 2011
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Sift flow: Dense correspondence across scenes and its applications
C. Liu, J. Yuen, and A. Torralba · 2011
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Semantic segmentation with second-order pooling
J. Carreira, R. Caseiro, J. Batista, and C. Sminchisescu · 2012
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Deep neural networks segment neuronal membranes in electron microscopy images
D. C. Ciresan, A. Giusti, L. M. Gambardella, and J. Schmidhuber · 2012
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Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
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Building high-level features using large scale unsupervised learning
Q. V. Le, R. Monga, M. Devin, K. Chen, G. S. Corrado, J. Dean, and A. Y. Ng · 2012
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Indoor segmentation and support inference from rgbd images
N. Silberman, D. Hoiem, P. Kohli, and R. Fergus · 2012
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Restoring an image taken through a window covered with dirt or rain
D. Eigen, D. Krishnan, and R. Fergus · 2013
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Learning hierarchical features for scene labeling
C. Farabet, C. Couprie, L. Najman, and Y. LeCun · 2013
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Perceptual organization and recognition of indoor scenes from RGB-D images
S. Gupta, P. Arbelaez, and J. Malik · 2013
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Finding things: Image parsing with regions and per-exemplar detectors
J. Tighe and S. Lazebnik · 2013
Simultaneous detection and segmentation
B. Hariharan, P. Arbeláez, R. Girshick, and J. Malik · 2014
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Spatial pyramid pooling in deep convolutional networks for visual recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2014
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Caffe: Convolutional architecture for fast feature embedding
Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. Girshick, S. Guadarrama, and T. Darrell · 2014
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Do convnets learn correspondence?
J. Long, N. Zhang, and T. Darrell · 2014
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The role of context for object detection and semantic segmentation in the wild
R. Mottaghi, X. Chen, X. Liu, N.-G. Cho, S.-W. Lee, S. Fidler, R. Urtasun, and A. Yuille · 2014
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Recurrent convolutional neural networks for scene labeling
P. H. Pinheiro and R. Collobert · 2014
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Cited alongside, same era.
Regularization of neural networks using dropconnect
L. Wan, M. Zeiler, S. Zhang, Y. L. Cun, and R. Fergus · 2013
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Convolutional feature masking for joint object and stuff segmentation
J. Dai, K. He, and J. Sun · 2014
Cited alongside, same era.
DeCAF: A deep convolutional activation feature for generic visual recognition
J. Donahue, Y. Jia, O. Vinyals, J. Hoffman, N. Zhang, E. Tzeng, and T. Darrell · 2014
Cited alongside, same era.
Depth map prediction from a single image using a multi-scale deep network
D. Eigen, C. Puhrsch, and R. Fergus · 2014
Cited alongside, same era.
Descriptor matching with convolutional neural networks: a comparison to SIFT
P. Fischer, A. Dosovitskiy, and T. Brox · 2014
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Rich feature hierarchies for accurate object detection and semantic segmentation
R. Girshick, J. Donahue, T. Darrell, and J. Malik · 2014
Cited alongside, same era.
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Overfeat: Integrated recognition, localization and detection using convolutional networks
P. Sermanet, D. Eigen, X. Zhang, M. Mathieu, R. Fergus, and Y. LeCun · 2014
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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
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Going deeper with convolutions
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich · 2014
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Joint training of a convolutional network and a graphical model for human pose estimation
J. Tompson, A. Jain, Y. LeCun, and C. Bregler · 2014
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Visualizing and understanding convolutional networks
M. D. Zeiler and R. Fergus · 2014
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Part-based r-cnns for fine-grained category detection
N. Zhang, J. Donahue, R. Girshick, and T. Darrell · 2014
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