-
1
-
-
0028392483
-
Learning long-term dependencies with gradient descent is difficult
-
1, 4
-
Y. Bengio, P. Simard, and P. Frasconi. Learning long-term dependencies with gradient descent is difficult. Neural Networks, IEEE Transactions on, 5 (2), 1994.
-
(1994)
Neural Networks, IEEE Transactions on
, vol.5
, Issue.2
-
-
Bengio, Y.1
Simard, P.2
Frasconi, P.3
-
4
-
-
5044219639
-
Super-resolution through neighbor embedding
-
2
-
H. Chang, D.-Y. Yeung, and Y. Xiong. Super-resolution through neighbor embedding. In CVPR, 2004.
-
(2004)
CVPR
-
-
Chang, H.1
Yeung, D.-Y.2
Xiong, Y.3
-
5
-
-
84977918054
-
Image superresolution using deep convolutional networks
-
1, 2, 3, 6, 7, 8
-
C. Dong, C. C. Loy, K. He, and X. Tang. Image superresolution using deep convolutional networks. TPAMI, 2014.
-
(2014)
TPAMI
-
-
Dong, C.1
Loy, C.C.2
He, K.3
Tang, X.4
-
6
-
-
85083953781
-
Understanding deep architectures using a recursive convolutional network
-
2
-
D. Eigen, J. Rolfe, R. Fergus, and Y. LeCun. Understanding deep architectures using a recursive convolutional network. In ICLR Workshop, 2014.
-
(2014)
ICLR Workshop
-
-
Eigen, D.1
Rolfe, J.2
Fergus, R.3
LeCun, Y.4
-
8
-
-
77953187337
-
Super-resolution from a single image
-
2
-
D. Glasner, S. Bagon, and M. Irani. Super-resolution from a single image. In ICCV, 2009.
-
(2009)
ICCV
-
-
Glasner, D.1
Bagon, S.2
Irani, M.3
-
9
-
-
84973911419
-
Delving deep into rectifiers: Surpassing human-level performance on imagenet classification
-
7
-
K. He, X. Zhang, S. Ren, and J. Sun. Delving deep into rectifiers: Surpassing human-level performance on imagenet classification. In ICCV, 2015.
-
(2015)
ICCV
-
-
He, K.1
Zhang, X.2
Ren, S.3
Sun, J.4
-
10
-
-
84959188745
-
Single image superresolution using transformed self-exemplars
-
2, 6, 7, 8
-
J.-B. Huang, A. Singh, and N. Ahuja. Single image superresolution using transformed self-exemplars. In CVPR, 2015.
-
(2015)
CVPR
-
-
Huang, J.-B.1
Singh, A.2
Ahuja, N.3
-
12
-
-
77951623771
-
Single-image super-resolution using sparse regression and natural image prior
-
2
-
K. I. Kim and Y. Kwon. Single-image super-resolution using sparse regression and natural image prior. TPAMI, 2010.
-
(2010)
TPAMI
-
-
Kim, K.I.1
Kwon, Y.2
-
13
-
-
84876231242
-
Imagenet classification with deep convolutional neural networks
-
1
-
A. Krizhevsky, I. Sutskever, and G. E. Hinton. Imagenet classification with deep convolutional neural networks. In NIPS, 2012.
-
(2012)
NIPS
-
-
Krizhevsky, A.1
Sutskever, I.2
Hinton, G.E.3
-
15
-
-
0032203257
-
Gradientbased learning applied to document recognition
-
5
-
Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner. Gradientbased learning applied to document recognition. Proceedings of the IEEE, 86 (11), 1998.
-
(1998)
Proceedings of the IEEE
, vol.86
, Issue.11
-
-
LeCun, Y.1
Bottou, L.2
Bengio, Y.3
Haffner, P.4
-
16
-
-
84943645147
-
-
arXiv preprint arXiv: 1409. 5185, 3, 4
-
C.-Y. Lee, S. Xie, P. Gallagher, Z. Zhang, and Z. Tu. Deeplysupervised nets. ArXiv preprint arXiv: 1409. 5185, 2014.
-
(2014)
Deeplysupervised Nets
-
-
Lee, C.-Y.1
Xie, S.2
Gallagher, P.3
Zhang, Z.4
Tu, Z.5
-
17
-
-
84959193001
-
Recurrent convolutional neural network for object recognition
-
2, 4
-
M. Liang and X. Hu. Recurrent convolutional neural network for object recognition. In CVPR, 2015.
-
(2015)
CVPR
-
-
Liang, M.1
Hu, X.2
-
19
-
-
84898409537
-
Low-complexity single-image super-resolution based on nonnegative neighbor embedding
-
2, 5, 7
-
C. G. Marco Bevilacqua, Aline Roumy and M.-L. A. Morel. Low-complexity single-image super-resolution based on nonnegative neighbor embedding. In BMVC, 2012.
-
(2012)
BMVC
-
-
Marco Bevilacqua, C.G.1
Roumy, A.2
Morel, M.-L.A.3
-
20
-
-
0034850577
-
A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics
-
7
-
D. Martin, C. Fowlkes, D. Tal, and J. Malik. A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics. In ICCV, 2001.
-
(2001)
ICCV
-
-
Martin, D.1
Fowlkes, C.2
Tal, D.3
Malik, J.4
-
21
-
-
84897497795
-
On the difficulty of training recurrent neural networks
-
4
-
R. Pascanu, T. Mikolov, and Y. Bengio. On the difficulty of training recurrent neural networks. In ICML, 2013.
-
(2013)
ICML
-
-
Pascanu, R.1
Mikolov, T.2
Bengio, Y.3
-
23
-
-
84959234116
-
Fast and accurate image upscaling with super-resolution forests
-
2, 6, 7, 8
-
S. Schulter, C. Leistner, and H. Bischof. Fast and accurate image upscaling with super-resolution forests. In CVPR, 2015.
-
(2015)
CVPR
-
-
Schulter, S.1
Leistner, C.2
Bischof, H.3
-
24
-
-
85083953063
-
Very deep convolutional networks for large-scale image recognition
-
1
-
K. Simonyan and A. Zisserman. Very deep convolutional networks for large-scale image recognition. In ICLR, 2015.
-
(2015)
ICLR
-
-
Simonyan, K.1
Zisserman, A.2
-
25
-
-
84877789646
-
Convolutional-recursive deep learning for 3d object classification
-
2
-
R. Socher, B. Huval, B. Bath, C. D. Manning, and A. Y. Ng. Convolutional-recursive deep learning for 3d object classification. In NIPS, 2012.
-
(2012)
NIPS
-
-
Socher, R.1
Huval, B.2
Bath, B.3
Manning, C.D.4
Ng, A.Y.5
-
26
-
-
84870715081
-
Semantic compositionality through recursive matrix-vector spaces
-
7
-
R. Socher, B. Huval, C. D. Manning, and A. Y. Ng. Semantic compositionality through recursive matrix-vector spaces. In EMNLP-CoNLL, 2012.
-
(2012)
EMNLP-CoNLL
-
-
Socher, R.1
Huval, B.2
Manning, C.D.3
Ng, A.Y.4
-
27
-
-
51949110386
-
Image super-resolution using gradient profile prior
-
2
-
J. Sun, Z. Xu, and H.-Y. Shum. Image super-resolution using gradient profile prior. In CVPR, 2008.
-
(2008)
CVPR
-
-
Sun, J.1
Xu, Z.2
Shum, H.-Y.3
-
28
-
-
84898792173
-
Anchored neighborhood regression for fast example-based super-resolution
-
2, 5, 7
-
R. Timofte, V. De, and L. V. Gool. Anchored neighborhood regression for fast example-based super-resolution. In ICCV, 2013.
-
(2013)
ICCV
-
-
Timofte, R.1
De, V.2
Gool, L.V.3
-
29
-
-
84932095280
-
A+: Adjusted anchored neighborhood regression for fast super-resolution
-
2, 5, 6, 7, 8
-
R. Timofte, V. De Smet, and L. Van Gool. A+: Adjusted anchored neighborhood regression for fast super-resolution. In ACCV, 2014.
-
(2014)
ACCV
-
-
Timofte, R.1
De Smet, V.2
Van Gool, L.3
-
31
-
-
78049312324
-
Image superresolution via sparse representation
-
2, 7
-
J. Yang, J. Wright, T. S. Huang, and Y. Ma. Image superresolution via sparse representation. TIP, 2010.
-
(2010)
TIP
-
-
Yang, J.1
Wright, J.2
Huang, T.S.3
Ma, Y.4
-
32
-
-
84855655878
-
On single image scaleup using sparse-representations
-
Springer, 2, 7
-
R. Zeyde, M. Elad, and M. Protter. On single image scaleup using sparse-representations. In Curves and Surfaces. Springer, 2012.
-
(2012)
Curves and Surfaces
-
-
Zeyde, R.1
Elad, M.2
Protter, M.3
|