-
1
-
-
0002021231
-
Matching pursuit of images
-
F. Bergeaud and S. Mallat. Matching Pursuit of Images. In ICIP, 1995.
-
(1995)
ICIP
-
-
Bergeaud, F.1
Mallat, S.2
-
3
-
-
77956502203
-
A theoretical analysis of feature pooling in visual recognition
-
Y.-L. Boureau, J. Ponce, and Y. LeCun. A Theoretical Analysis of Feature Pooling in Visual Recognition. In ICML, 2010.
-
(2010)
ICML
-
-
Boureau, Y.-L.1
Ponce, J.2
LeCun, Y.3
-
4
-
-
80052870578
-
Discriminative learning of local image descriptors
-
M. Brown, G. Hua, and S. Winder. Discriminative Learning of Local Image Descriptors. PAMI, 2010.
-
(2010)
PAMI
-
-
Brown, M.1
Hua, G.2
Winder, S.3
-
5
-
-
7044231546
-
An iterative thresholding algorithm for linear inverse problems with a sparsity constraint
-
I. Daubechies, M. Defrise, and C. D. Mol. An iterative thresholding algorithm for linear inverse problems with a sparsity constraint. CPAM, 2004.
-
(2004)
CPAM
-
-
Daubechies, I.1
Defrise, M.2
Mol, C.D.3
-
6
-
-
33645712892
-
Compressed sensing
-
D. L. Donoho. Compressed Sensing. TIT, 2006.
-
(2006)
TIT
-
-
Donoho, D.L.1
-
7
-
-
84932617705
-
Learning generative visual models from few training examples: An incremental bayesian approach tested on 101 object categories
-
L. Fei-Fei, R. Fergus, and P. Perona. Learning Generative Visual Models from Few Training Examples: An Incremental Bayesian Approach Tested on 101 Object Categories. In CVPR, 2004.
-
(2004)
CVPR
-
-
Fei-Fei, L.1
Fergus, R.2
Perona, P.3
-
8
-
-
75449104637
-
Learning to represent visual input
-
G. E. Hinton. Learning to Represent Visual Input. RSTB, 2010.
-
(2010)
RSTB
-
-
Hinton, G.E.1
-
9
-
-
50649113227
-
Discriminant embedding for local image descriptors
-
G. Hua, M. Brown, and S. Winder. Discriminant Embedding for Local Image Descriptors. In ICCV, 2007.
-
(2007)
ICCV
-
-
Hua, G.1
Brown, M.2
Winder, S.3
-
10
-
-
33645410496
-
Receptive fields, binocular interaction and functional architecture in the cat's visual cortex
-
D. H. Hubel and T. N. Wiesel. Receptive Fields, Binocular Interaction and Functional Architecture in the Cat's Visual Cortex. JPHYSIO, 1962.
-
(1962)
JPHYSIO
-
-
Hubel, D.H.1
Wiesel, T.N.2
-
12
-
-
77953183471
-
What is the best multi-stage architecture for object recognition?
-
K. Jarrett, K. Kavukcuoglu, M. A. Ranzato, and Y. LeCun. What Is the Best Multi-Stage Architecture for Object Recognition? In ICCV, 2009.
-
(2009)
ICCV
-
-
Jarrett, K.1
Kavukcuoglu, K.2
Ranzato, M.A.3
LeCun, Y.4
-
13
-
-
70049083257
-
Fast inference in sparse coding algorithms with applications to object recognition
-
K. Kavukcuoglu, M. A. Ranzato, and Y. LeCun. Fast Inference in Sparse Coding Algorithms With Applications to Object Recognition. Technical report, NYU, 2008.
-
(2008)
Technical Report, NYU
-
-
Kavukcuoglu, K.1
Ranzato, M.A.2
LeCun, Y.3
-
15
-
-
79959327338
-
Convolutional deep belief networks on CIFAR-10
-
A. Krizhevsky. Convolutional Deep Belief Networks on CIFAR-10. Technical report, UOFT, 2010.
-
(2010)
Technical Report, UOFT
-
-
Krizhevsky, A.1
-
16
-
-
33845572523
-
Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories
-
S. Lazebnik, C. Schmid, and J. Ponce. Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories. In CVPR, 2006.
-
(2006)
CVPR
-
-
Lazebnik, S.1
Schmid, C.2
Ponce, J.3
-
17
-
-
0032203257
-
Gradient-based learning applied to document recognition
-
Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner. Gradient-Based Learning Applied to Document Recognition. PIEEE, 1998.
-
(1998)
PIEEE
-
-
LeCun, Y.1
Bottou, L.2
Bengio, Y.3
Haffner, P.4
-
18
-
-
56449086627
-
Sparse deep belief net model for visual area V2
-
H. Lee, C. Ekanadham, and A. Y. Ng. Sparse Deep Belief Net Model for Visual Area V2. In NIPS, 2007.
-
(2007)
NIPS
-
-
Lee, H.1
Ekanadham, C.2
Ng, A.Y.3
-
19
-
-
71149119164
-
Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
-
H. Lee, R. Grosse, R. Ranganath, and A. Y. Ng. Convolutional Deep Belief Networks for Scalable Unsupervised Learning of Hierarchical Representations. In ICML, 2009.
-
(2009)
ICML
-
-
Lee, H.1
Grosse, R.2
Ranganath, R.3
Ng, A.Y.4
-
20
-
-
0035358496
-
Representing and recognizing the visual appearance of materials using three-dimensional textons
-
T. Leung and J. Malik. Representing and Recognizing the Visual Appearance of Materials Using Three-Dimensional Textons. IJCV, 2001.
-
(2001)
IJCV
-
-
Leung, T.1
Malik, J.2
-
21
-
-
3042535216
-
Distinctive image features from scale-invariants keypoints
-
D. G. Lowe. Distinctive Image Features from Scale-Invariants Keypoints. IJCV, 2004.
-
(2004)
IJCV
-
-
Lowe, D.G.1
-
22
-
-
51949103923
-
Discriminative learned dictionaries for local image analysis
-
J. Mairal, F. Bach, J. Ponce, G. Sapiro, and A. Zisserman. Discriminative Learned Dictionaries for Local Image Analysis. In CVPR, 2008.
-
(2008)
CVPR
-
-
Mairal, J.1
Bach, F.2
Ponce, J.3
Sapiro, G.4
Zisserman, A.5
-
23
-
-
77952739016
-
Non-local sparse models for image restoration
-
J. Mairal, F. Bach, J. Ponce, G. Sapiro, and A. Zisserman. Non-Local Sparse Models for Image Restoration. In ICCV, 2009.
-
(2009)
ICCV
-
-
Mairal, J.1
Bach, F.2
Ponce, J.3
Sapiro, G.4
Zisserman, A.5
-
24
-
-
80052890481
-
Sparse coding with an overcomplete basis set: A strategy employed by V1?
-
B. A. Olshausen and D. J. Field. Sparse Coding With an Overcomplete Basis Set: A Strategy Employed by V1? VISR, 1997.
-
(1997)
VISR
-
-
Olshausen, B.A.1
Field, D.J.2
-
25
-
-
38949193299
-
Why is real-world visual object recognition hard?
-
N. Pinto, D. D. Cox, and J. J. DiCarlo. Why Is Real-World Visual Object Recognition Hard? PLoS, 2008.
-
(2008)
PLoS
-
-
Pinto, N.1
Cox, D.D.2
DiCarlo, J.J.3
-
26
-
-
70049094447
-
Sparse feature learning for deep belief networks
-
M. A. Ranzato, Y.-L. Boureau, and Y. LeCun. Sparse Feature Learning for Deep Belief Networks. In NIPS, 2007.
-
(2007)
NIPS
-
-
Ranzato, M.A.1
Boureau, Y.-L.2
LeCun, Y.3
-
27
-
-
77955989954
-
Modeling pixel means and covariances using factorized third-order Boltzmann machines
-
M. A. Ranzato and G. E. Hinton. Modeling Pixel Means and Covariances Using Factorized Third-Order Boltzmann Machines. In CVPR, 2010.
-
(2010)
CVPR
-
-
Ranzato, M.A.1
Hinton, G.E.2
-
28
-
-
34948870900
-
Unsupervised learning of invariant feature hierarchies with applications to object recognition
-
M. A. Ranzato, F.-J. Huang, Y. Boureau, and Y. LeCun. Unsupervised Learning of Invariant Feature Hierarchies With Applications to Object Recognition. In CVPR, 2007.
-
(2007)
CVPR
-
-
Ranzato, M.A.1
Huang, F.-J.2
Boureau, Y.3
LeCun, Y.4
-
29
-
-
85112276587
-
Efficient learning of sparse representations with an energy-based model
-
M. A. Ranzato, C. Poultney, S. Chopra, and Y. LeCun. Efficient Learning of Sparse Representations With an Energy-Based Model. In NIPS, 2006.
-
(2006)
NIPS
-
-
Ranzato, M.A.1
Poultney, C.2
Chopra, S.3
LeCun, Y.4
-
30
-
-
33847380121
-
Robust object recognition with cortex-like mechanisms
-
T. Serre, L. Wolf, S. Bileschi, M. Riesenhuber, and T. Poggio. Robust Object Recognition With Cortex-Like Mechanisms. PAMI, 2007.
-
(2007)
PAMI
-
-
Serre, T.1
Wolf, L.2
Bileschi, S.3
Riesenhuber, M.4
Poggio, T.5
-
31
-
-
77949875753
-
DAISY: An efficient dense descriptor applied to wide-baseline stereo
-
E. Tola, V. Lepetit, and P. Fua. DAISY: An Efficient Dense Descriptor Applied to Wide-Baseline Stereo. PAMI, 2010.
-
(2010)
PAMI
-
-
Tola, E.1
Lepetit, V.2
Fua, P.3
-
32
-
-
54749092170
-
80 Million tiny images: A large dataset for non-parametric object and scene recognition
-
A. Torralba, R. Fergus, and W. T. Freeman. 80 Million Tiny Images: A Large Dataset for Non-Parametric Object and Scene Recognition. PAMI, 2008.
-
(2008)
PAMI
-
-
Torralba, A.1
Fergus, R.2
Freeman, W.T.3
-
33
-
-
0034681515
-
Sparse coding and decorrelation in primary visual cortex during natural vision
-
W. E. Vinje and J. L. Gallant. Sparse Coding and Decorrelation in Primary Visual Cortex During Natural Vision. SCIENCE, 2000.
-
(2000)
Science
-
-
Vinje, W.E.1
Gallant, J.L.2
-
34
-
-
77952717202
-
Sparse representation for computer vision and pattern recognition
-
J. Wright, Y. Ma, J. Mairal, G. Sapiro, T. S. Huang, and S. Yan. Sparse Representation for Computer Vision and Pattern Recognition. PIEEE, 2010.
-
(2010)
PIEEE
-
-
Wright, J.1
Ma, Y.2
Mairal, J.3
Sapiro, G.4
Huang, T.S.5
Yan, S.6
-
35
-
-
70450209196
-
Linear spatial pyramid matching using sparse coding for image classification
-
J. Yang, K. Yu, Y. Gong, and T. Huang. Linear Spatial Pyramid Matching Using Sparse Coding for Image Classification. In CVPR, 2009.
-
(2009)
CVPR
-
-
Yang, J.1
Yu, K.2
Gong, Y.3
Huang, T.4
-
36
-
-
77956510751
-
Improved local coordinate coding using local tangents
-
K. Yu and T. Zhang. Improved Local Coordinate Coding Using Local Tangents. In ICML, 2010.
-
(2010)
ICML
-
-
Yu, K.1
Zhang, T.2
|