-
1
-
-
51949090223
-
Defense of nearest-neighbor based image classification
-
7
-
O Boiman, E Shechtman, andMIrani. In defense of nearest-neighbor based image classification. In CVPR, 2008. 7
-
(2008)
CVPR
-
-
Boiman, O.1
Shechtman, E.2
Irani, M.3
-
3
-
-
84856649187
-
Ask the locals: Multi-way local pooling for image recognition
-
3, 7, 8
-
Y Boureau, N Le Roux, F Bach, J Ponce, and Y LeCun. Ask the locals: multi-way local pooling for image recognition. In ICCV, 2011. 3, 7, 8
-
(2011)
ICCV
-
-
Boureau, Y.1
Le Roux, N.2
Bach, F.3
Ponce, J.4
Lecun, Y.5
-
4
-
-
77956502203
-
A theoretical analysis of feature pooling in visual recognition
-
1, 3
-
Y Boureau and J Ponce. A theoretical analysis of feature pooling in visual recognition. In ICML, 2010. 1, 3
-
(2010)
ICML
-
-
Boureau, Y.1
Ponce, J.2
-
5
-
-
79957835935
-
High-performance neural networks for visual object classification
-
7
-
DC Cireşan, U Meier, J Masci, LM Gambardella, and J Schmidhuber. High-performance neural networks for visual object classification. ArXiv e-prints, 2011. 7
-
(2011)
ArXiv E-prints
-
-
Cireşan, D.C.1
Meier, U.2
Masci, J.3
Gambardella, L.M.4
Schmidhuber, J.5
-
6
-
-
80053446757
-
An analysis of single-layer networks in unsupervised feature learning
-
1, 2, 3, 5, 6, 7
-
A Coates, H Lee, and AY Ng. An analysis of single-layer networks in unsupervised feature learning. In AISTATS, 2010. 1, 2, 3, 5, 6, 7
-
(2010)
AISTATS
-
-
Coates, A.1
Lee, H.2
Ng, A.Y.3
-
7
-
-
85162494200
-
Selecting receptive fields in deep networks
-
1
-
A. Coates and A.Y. Ng. Selecting receptive fields in deep networks. In NIPS, 2011. 1
-
(2011)
NIPS
-
-
Coates, A.1
Ng, A.Y.2
-
8
-
-
85162494200
-
Selecting receptive fields in deep networks
-
7
-
A Coates and AY Ng. Selecting receptive fields in deep networks. In NIPS, 2011. 7
-
(2011)
NIPS
-
-
Coates, A.1
Ng, A.Y.2
-
9
-
-
80053442434
-
The importance of encoding versus training with sparse coding and vector quantization
-
1, 2, 5, 7
-
A Coates and AY Ng. The importance of encoding versus training with sparse coding and vector quantization. In ICML, 2011. 1, 2, 5, 7
-
(2011)
ICML
-
-
Coates, A.1
Ng, A.Y.2
-
10
-
-
33645146449
-
Histograms of oriented gradients for human detection
-
1
-
N Dalal. Histograms of oriented gradients for human detection. In CVPR, 2005. 1
-
(2005)
CVPR
-
-
Dalal, N.1
-
11
-
-
77951298115
-
The PASCAL visual object classes (VOC) challenge
-
1
-
M Everingham, L Van Gool, CKI Williams, J Winn, and A Zisserman. The PASCAL visual object classes (VOC) challenge. IJCV, 88(2):303-338, 2010. 1
-
(2010)
IJCV
, vol.88
, Issue.2
, pp. 303-338
-
-
Everingham, M.1
Van Gool, L.2
Williams, C.K.I.3
Winn, J.4
Zisserman, A.5
-
12
-
-
80052872055
-
Geometric Lp-norm feature pooling for image classification
-
7, 8
-
J Feng, B Ni, Q Tian, and S Yan. Geometric Lp-norm Feature Pooling for Image Classification. In CVPR, 2011. 7, 8
-
(2011)
CVPR
-
-
Feng, J.1
Ni, B.2
Tian, Q.3
Yan, S.4
-
13
-
-
33645410496
-
Receptive fields, binocular interaction and functional architecture in the cat's visual cortex
-
1
-
DH Hubel and TN Wiesel. Receptive fields, binocular interaction and functional architecture in the cat's visual cortex. The Journal of Physiology, 160:106-154, 1962. 1
-
(1962)
The Journal of Physiology
, vol.160
, pp. 106-154
-
-
Hubel, D.H.1
Wiesel, T.N.2
-
15
-
-
77953183471
-
What is the best multi-stage architecture for object recognition?
-
7
-
K Jarrett, K Kavukcuoglu, MA Ranzato, and Y LeCun. What is the best multi-stage architecture for object recognition? In ICCV, 2009. 7
-
(2009)
ICCV
-
-
Jarrett, K.1
Kavukcuoglu, K.2
Ranzato, M.3
Lecun, Y.4
-
16
-
-
80052906316
-
A probabilistic model for recursive factorized image features
-
7
-
S Karayev, M Fritz, S Fidler, and T Darrell. A probabilistic model for recursive factorized image features. In CVPR, 2011. 7
-
(2011)
CVPR
-
-
Karayev, S.1
Fritz, M.2
Fidler, S.3
Darrell, T.4
-
17
-
-
0032672025
-
The structure of locally orderless images
-
1
-
JJ Koenderink and AJ van Doorn. The structure of locally orderless images. IJCV, 31(2/3):159-168, 1999. 1
-
(1999)
IJCV
, vol.31
, Issue.2-3
, pp. 159-168
-
-
Koenderink, J.J.1
Van Doorn, A.J.2
-
19
-
-
56449124824
-
Simple method for high-performance digit recognition based on sparse coding
-
7
-
K Labusch, E Barth, and T Martinetz. Simple method for high-performance digit recognition based on sparse coding. IEEE TNN, 19(11):1985-1989, 2008. 7
-
(2008)
IEEE TNN
, vol.19
, Issue.11
, pp. 1985-1989
-
-
Labusch, K.1
Barth, E.2
Martinetz, T.3
-
20
-
-
33947170570
-
A trainable feature extractor for handwritten digit recognition
-
7
-
F Lauer, CY Suen, and G Bloch. A trainable feature extractor for handwritten digit recognition. Pattern Recognition, 40(6):1816-1824, 2007. 7
-
(2007)
Pattern Recognition
, vol.40
, Issue.6
, pp. 1816-1824
-
-
Lauer, F.1
Suen, C.Y.2
Bloch, G.3
-
21
-
-
33845572523
-
Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories
-
1, 3, 7
-
S Lazebnik, C Schmid, and J Ponce. Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories. In CVPR, 2006. 1, 3, 7
-
(2006)
CVPR
-
-
Lazebnik, S.1
Schmid, C.2
Ponce, J.3
-
22
-
-
3042535216
-
Distinctive image features from scale-invariant keypoints
-
1
-
D Lowe. Distinctive image features from scale-invariant keypoints. IJCV, 2004. 1
-
(2004)
IJCV
-
-
Lowe, D.1
-
23
-
-
76749107542
-
Online learning for matrix factorization and sparse coding
-
1
-
J Mairal, F Bach, J Ponce, and G Sapiro. Online learning for matrix factorization and sparse coding. JMLR, 11:19-60, 2010. 1
-
(2010)
JMLR
, vol.11
, pp. 19-60
-
-
Mairal, J.1
Bach, F.2
Ponce, J.3
Sapiro, G.4
-
24
-
-
0030779611
-
Sparse coding with an overcomplete basis set: A strategy employed by V1?
-
1
-
B Olshausen and DJ Field. Sparse coding with an overcomplete basis set: a strategy employed by V1? Vision research, 37(23):3311-3325, 1997. 1
-
(1997)
Vision Research
, vol.37
, Issue.23
, pp. 3311-3325
-
-
Olshausen, B.1
Field, D.J.2
-
25
-
-
1942418470
-
Grafting: Fast, incremental feature selection by gradient descent in function space
-
4, 6
-
S Perkins, K Lacker, and J Theiler. Grafting: fast, incremental feature selection by gradient descent in function space. JMLR, 3:1333-1356, 2003. 4, 6
-
(2003)
JMLR
, vol.3
, pp. 1333-1356
-
-
Perkins, S.1
Lacker, K.2
Theiler, J.3
-
26
-
-
51949094374
-
Transfer learning for image classification with sparse prototype representations
-
4
-
A Quattoni, M Collins, and T Darrell. Transfer learning for image classification with sparse prototype representations. In CVPR, 2008. 4
-
(2008)
CVPR
-
-
Quattoni, A.1
Collins, M.2
Darrell, T.3
-
27
-
-
34948870900
-
Unsupervised learning of invariant feature hierarchies with applications to object recognition
-
7
-
MA Ranzato, FJ Huang, Y Boureau, and Y LeCun. Unsupervised learning of invariant feature hierarchies with applications to object recognition. In CVPR, 2007. 7
-
(2007)
CVPR
-
-
Ranzato, M.1
Huang, F.J.2
Boureau, Y.3
Lecun, Y.4
-
28
-
-
80052904079
-
Are sparse representations really relevant for image classification?
-
1
-
R Rigamonti, MA Brown, and V Lepetit. Are sparse representations really relevant for image classification? In CVPR, 2011. 1
-
(2011)
CVPR
-
-
Rigamonti, R.1
Brown, M.2
Lepetit, V.3
-
29
-
-
51949118201
-
Structure learning in random fields for heart motion abnormality detection
-
4
-
M Schmidt, K Murphy, G Fung, and R Rosales. Structure learning in random fields for heart motion abnormality detection. In CVPR, 2008. 4
-
(2008)
CVPR
-
-
Schmidt, M.1
Murphy, K.2
Fung, G.3
Rosales, R.4
-
30
-
-
0001287271
-
Regression shrinkage and selection via the lasso
-
6
-
R Tibshirani. Regression shrinkage and selection via the lasso. JRSS Series B, pages 267-288, 1996. 6
-
(1996)
JRSS Series B
, pp. 267-288
-
-
Tibshirani, R.1
-
31
-
-
77955996870
-
Locality-constrained linear coding for image classification
-
1, 7
-
J Wang, J Yang, K Yu, F Lv, T Huang, and Y Gong. Locality-constrained linear coding for image classification. In CVPR, 2010. 1, 7
-
(2010)
CVPR
-
-
Wang, J.1
Yang, J.2
Yu, K.3
Lv, F.4
Huang, T.5
Gong, Y.6
-
32
-
-
34948826471
-
Learning local image descriptors
-
1
-
SWinder andMBrown. Learning local image descriptors. In CVPR, 2007. 1
-
(2007)
CVPR
-
-
Winder, S.1
Brown, M.2
-
33
-
-
70450209196
-
Linear spatial pyramid matching using sparse coding for image classification
-
1, 3, 7
-
J Yang, K Yu, and Y Gong. Linear spatial pyramid matching using sparse coding for image classification. In CVPR, 2009. 1, 3, 7
-
(2009)
CVPR
-
-
Yang, J.1
Yu, K.2
Gong, Y.3
-
34
-
-
80052906448
-
Efficient highly over-complete sparse coding using a mixture model
-
1, 8
-
J Yang, K Yu, and T Huang. Efficient highly over-complete sparse coding using a mixture model. In ECCV, 2010. 1, 8
-
(2010)
ECCV
-
-
Yang, J.1
Yu, K.2
Huang, T.3
-
35
-
-
77956510751
-
Improved local coordinate coding using local tangents
-
7
-
K Yu and T Zhang. Improved local coordinate coding using local tangents. In ICML, 2010. 7
-
(2010)
ICML
-
-
Yu, K.1
Zhang, T.2
-
36
-
-
84856686379
-
Adaptive deconvolutional networks for mid and high level feature learning
-
7
-
MD Zeiler, GW Taylor, and R Fergus. Adaptive deconvolutional networks for mid and high level feature learning. In ICCV, 2011. 7
-
(2011)
ICCV
-
-
Zeiler, M.D.1
Taylor, G.W.2
Fergus, R.3
-
37
-
-
16244401458
-
Regularization and variable selection via the elastic net
-
4
-
H Zou and T Hastie. Regularization and variable selection via the elastic net. JRSS, 67(2):301-320, 2005. 4
-
(2005)
JRSS
, vol.67
, Issue.2
, pp. 301-320
-
-
Zou, H.1
Hastie, T.2
|