-
2
-
-
0002291365
-
Generalization and network design strategies
-
Y. LeCun, “Generalization and network design strategies,” in Connectionism in Perspective (Elsevier, 1989), pp. 143–155.
-
(1989)
Connectionism in Perspective
, pp. 143-155
-
-
Lecun, Y.1
-
4
-
-
84937522268
-
Going deeper with convolu-tions
-
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich, “Going deeper with convolu-tions,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2015), pp. 1–9.
-
(2015)
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition
, pp. 1-9
-
-
Szegedy, C.1
Liu, W.2
Jia, Y.3
Sermanet, P.4
Reed, S.5
Anguelov, D.6
Erhan, D.7
Vanhoucke, V.8
Rabinovich, A.9
-
5
-
-
84986274465
-
Deep residual learning for image recognition
-
K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2016), pp. 770–778.
-
(2016)
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition
, pp. 770-778
-
-
He, K.1
Zhang, X.2
Ren, S.3
Sun, J.4
-
6
-
-
0016758101
-
Cognitron: A self-organizing multilayered neural net-work
-
K. Fukushima, “Cognitron: a self-organizing multilayered neural net-work,” Biol. Cybernet. 20, 121–136 (1975).
-
(1975)
Biol. Cybernet.
, vol.20
, pp. 121-136
-
-
Fukushima, K.1
-
8
-
-
0022471098
-
Learning representations by back-propagating errors
-
D. E. Rumelhart, G. E. Hinton, and R. J. Williams, “Learning representations by back-propagating errors,” Nature 5323, 533–536 (1986).
-
(1986)
Nature
, vol.5323
, pp. 533-536
-
-
Rumelhart, D.E.1
Hinton, G.E.2
Williams, R.J.3
-
9
-
-
84872543023
-
Efficient backprop
-
Y. A. LeCun, L. Bottou, G. B. Orr, and K.-R. Müller, “Efficient backprop,” in Neural Networks: Tricks of the Trade (Springer, 2012), pp. 9–48.
-
(2012)
Neural Networks: Tricks of the Trade
, pp. 9-48
-
-
Lecun, Y.A.1
Bottou, L.2
Orr, G.B.3
Müller, K.-R.4
-
10
-
-
84924051598
-
Human-level control through deep reinforcement learning
-
V. Mnih, K. Kavukcuoglu, D. Silver, A. Rusu, J. Veness, M. Bellemare, A. Graves, M. Riedmiller, A. Fidjeland, G. Ostrovski, S. Petersen, C. Beattie, A. Sadik, I. Antonoglou, H. King, D. Kumaran, D. Wierstra, S. Legg, and D. Hassabis, “Human-level control through deep reinforcement learning,” Nature 518, 529–533 (2015).
-
(2015)
Nature
, vol.518
, pp. 529-533
-
-
Mnih, V.1
Kavukcuoglu, K.2
Silver, D.3
Rusu, A.4
Veness, J.5
Bellemare, M.6
Graves, A.7
Riedmiller, M.8
Fidjeland, A.9
Ostrovski, G.10
Petersen, S.11
Beattie, C.12
Sadik, A.13
Antonoglou, I.14
King, H.15
Kumaran, D.16
Wierstra, D.17
Legg, S.18
Hassabis, D.19
-
11
-
-
84963949906
-
Mastering the game of go with deep neural networks and tree search
-
D. Silver, A. Huang, C. Maddison, A. Guez, L. Sifre, G. van den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot, S. Dieleman, D. Grewe, J. Nham, N. Kalchbrenner, I. Sutskever, T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel, and D. Hassabis, “Mastering the game of go with deep neural networks and tree search,” Nature 529, 484–489 (2016).
-
(2016)
Nature
, vol.529
, pp. 484-489
-
-
Silver, D.1
Huang, A.2
Maddison, C.3
Guez, A.4
Sifre, L.5
Van Den Driessche, G.6
Schrittwieser, J.7
Antonoglou, I.8
Panneershelvam, V.9
Lanctot, M.10
Dieleman, S.11
Grewe, D.12
Nham, J.13
Kalchbrenner, N.14
Sutskever, I.15
Lillicrap, T.16
Leach, M.17
Kavukcuoglu, K.18
Graepel, T.19
Hassabis, D.20
more..
-
12
-
-
85015901563
-
Learning to generate chairs, tables and cars with convolutional networks
-
A. Dosovitskiy, J. T. Springenberg, M. Tatarchenko, and T. Brox, “Learning to generate chairs, tables and cars with convolutional networks,” IEEE Trans. Pattern Anal. Mach. Intell. 39, 692–705 (2017).
-
(2017)
IEEE Trans. Pattern Anal. Mach. Intell
, vol.39
, pp. 692-705
-
-
Dosovitskiy, A.1
Springenberg, J.T.2
Tatarchenko, M.3
Brox, T.4
-
13
-
-
84930630277
-
Deep learning
-
Y. LeCun, Y. Bengio, and G. Hinton, “Deep learning,” Nature 521, 436–444 (2015).
-
(2015)
Nature
, vol.521
, pp. 436-444
-
-
Lecun, Y.1
Bengio, Y.2
Hinton, G.3
-
15
-
-
84906484697
-
Learning a deep convolutional network for image super-resolution
-
C. Dong, C. C. Loy, K. He, and X. Tang, “Learning a deep convolutional network for image super-resolution,” in European Conference on Computer Vision (Springer, 2014), pp. 184–199.
-
(2014)
European Conference on Computer Vision
, pp. 184-199
-
-
Dong, C.1
Loy, C.C.2
He, K.3
Tang, X.4
-
16
-
-
84937878882
-
Deep convolutional neural network for image deconvolution
-
L. Xu, J. S. Ren, C. Liu, and J. Jia, “Deep convolutional neural network for image deconvolution,” in Advances in Neural Information Processing Systems (2014), pp. 1790–1798.
-
(2014)
Advances in Neural Information Processing Systems
, pp. 1790-1798
-
-
Xu, L.1
Ren, J.S.2
Liu, C.3
Jia, J.4
-
17
-
-
84959239596
-
Learning a convolutional neural network for non-uniform motion blur removal
-
J. Sun, W. Cao, Z. Xu, and J. Ponce, “Learning a convolutional neural network for non-uniform motion blur removal,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2015), pp. 769–777.
-
(2015)
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition
, pp. 769-777
-
-
Sun, J.1
Cao, W.2
Xu, Z.3
Ponce, J.4
-
19
-
-
0015327061
-
A practical algorithm for the determination of the phase from image and diffraction plane pictures
-
R. Gerchberg and W. Saxton, “A practical algorithm for the determination of the phase from image and diffraction plane pictures,” Optik 35, 237–246 (1972).
-
(1972)
Optik
, vol.35
, pp. 237-246
-
-
Gerchberg, R.1
Saxton, W.2
-
20
-
-
0017985106
-
Reconstruction of an object from the modulus of its Fourier transform
-
J. R. Fienup, “Reconstruction of an object from the modulus of its Fourier transform,” Opt. Lett. 3, 27–29 (1978).
-
(1978)
Opt. Lett.
, vol.3
, pp. 27-29
-
-
Fienup, J.R.1
-
21
-
-
0002425705
-
Digital image formation from electronically detected holograms
-
J. W. Goodman and R. Lawrence, “Digital image formation from electronically detected holograms,” Appl. Phys. Lett. 11, 77–79 (1967).
-
(1967)
Appl. Phys. Lett.
, vol.11
, pp. 77-79
-
-
Goodman, J.W.1
Lawrence, R.2
-
22
-
-
0020849487
-
Deterministic phase retrieval: A Green’s function solu-tion
-
M. R. Teague, “Deterministic phase retrieval: a Green’s function solu-tion,” J. Opt. Soc. Am. 73, 1434–1441 (1983).
-
(1983)
J. Opt. Soc. Am.
, vol.73
, pp. 1434-1441
-
-
Teague, M.R.1
-
23
-
-
0021375095
-
Phase imaging by the transport equation of intensity
-
N. Streibl, “Phase imaging by the transport equation of intensity,” Opt. Commun. 49, 6–10 (1984).
-
(1984)
Opt. Commun.
, vol.49
, pp. 6-10
-
-
Streibl, N.1
-
25
-
-
0000418073
-
On the stability of inverse problems
-
A. N. Tikhonov, “On the stability of inverse problems,” Dokl. Akad. Nauk SSSR 39, 195–198 (1943).
-
(1943)
Dokl. Akad. Nauk SSSR
, vol.39
, pp. 195-198
-
-
Tikhonov, A.N.1
-
27
-
-
85032750937
-
An introduction to compressive sam-pling
-
E. J. Candès and M. B. Wakin, “An introduction to compressive sam-pling,” IEEE Signal Process. Mag. 25, 21–30 (2008).
-
(2008)
IEEE Signal Process. Mag.
, vol.25
, pp. 21-30
-
-
Candès, E.J.1
Wakin, M.B.2
-
29
-
-
0037418225
-
Optimally sparse representation in general (Nonorthogonal) dictionaries via l1 minimization
-
D. L. Donoho and M. Elad, “Optimally sparse representation in general (nonorthogonal) dictionaries via l1 minimization,” Proc. Natl. Acad. Sci. USA 100, 2197–2202 (2003).
-
(2003)
Proc. Natl. Acad. Sci. USA
, vol.100
, pp. 2197-2202
-
-
Donoho, D.L.1
Elad, M.2
-
30
-
-
84859083930
-
Robust image deblurring with an inaccurate blur kernel
-
H. Ji and K. Wang, “Robust image deblurring with an inaccurate blur kernel,” IEEE Trans. Image Process. 21, 1624–1634 (2012).
-
(2012)
IEEE Trans. Image Process.
, vol.21
, pp. 1624-1634
-
-
Ji, H.1
Wang, K.2
-
31
-
-
0020118274
-
Neural networks and physical systems with emergent collective computational abilities
-
J. J. Hopfield, “Neural networks and physical systems with emergent collective computational abilities,” Proc. Natl. Acad. Sci. USA 79, 2554–2558 (1982).
-
(1982)
Proc. Natl. Acad. Sci. USA
, vol.79
, pp. 2554-2558
-
-
Hopfield, J.J.1
-
32
-
-
84975551204
-
Optical implementation of the Hopfield model for two-dimensional associative memory
-
J.-S. Jang, S.-W. Jung, S.-Y. Lee, and S.-Y. Shin, “Optical implementation of the Hopfield model for two-dimensional associative memory,” Opt. Lett. 13, 248–250 (1988).
-
(1988)
Opt. Lett.
, vol.13
, pp. 248-250
-
-
Jang, J.-S.1
Jung, S.-W.2
Lee, S.-Y.3
Shin, S.-Y.4
-
33
-
-
84977655531
-
Learning-based imaging through scattering media
-
R. Horisaki, R. Takagi, and J. Tanida, “Learning-based imaging through scattering media,” Opt. Express 24, 13738–13743 (2016).
-
(2016)
Opt. Express
, vol.24
, pp. 13738-13743
-
-
Horisaki, R.1
Takagi, R.2
Tanida, J.3
-
34
-
-
77749289153
-
Measuring the transmission matrix in optics: An approach to the study and control of light propagation in disordered media
-
S. Popoff, G. Lerosey, R. Carminati, M. Fink, A. Boccara, and S. Gigan, “Measuring the transmission matrix in optics: an approach to the study and control of light propagation in disordered media,” Phys. Rev. Lett. 104, 100601 (2010).
-
(2010)
Phys. Rev. Lett.
, vol.104
, pp. 100601
-
-
Popoff, S.1
Lerosey, G.2
Carminati, R.3
Fink, M.4
Boccara, A.5
Gigan, S.6
-
35
-
-
85028465490
-
-
S. Popoff, G. Lerosey, M. Fink, A. C. Boccara, and S. Gigan, “Image transmission through an opaque material,” arXiv:1005.0532 (2010).
-
(2010)
Image Transmission through an Opaque Material
-
-
Popoff, S.1
Lerosey, G.2
Fink, M.3
Boccara, A.C.4
Gigan, S.5
-
36
-
-
84937922745
-
Learning approach to optical tomography
-
U. S. Kamilov, I. N. Papadopoulos, M. H. Shoreh, A. Goy, C. Vonesch, M. Unser, and D. Psaltis, “Learning approach to optical tomography,” Optica 2, 517–522 (2015).
-
(2015)
Optica
, vol.2
, pp. 517-522
-
-
Kamilov, U.S.1
Papadopoulos, I.N.2
Shoreh, M.H.3
Goy, A.4
Vonesch, C.5
Unser, M.6
Psaltis, D.7
-
37
-
-
85029853498
-
Holographic deep learning for rapid optical screening of anthrax spores
-
Y. Jo, S. Park, J. Jung, J. Yoon, H. Joo, M.-H. Kim, S.-J. Jo, M. C. Choi, S. Y. Lee, and Y. Park, “Holographic deep learning for rapid optical screening of anthrax spores,” BioRxiv (2017), 109108.
-
(2017)
Biorxiv
-
-
Jo, Y.1
Park, S.2
Jung, J.3
Yoon, J.4
Joo, H.5
Kim, M.-H.6
Jo, S.-J.7
Choi, M.C.8
Lee, S.Y.9
Park, Y.10
-
38
-
-
85023170573
-
Deep convolutional neural network for inverse problems in imaging
-
K. H. Jin, M. T. McCann, E. Froustey, and M. Unser, “Deep convolutional neural network for inverse problems in imaging,” IEEE Trans. Image Process. 26, 4509–4522 (2017).
-
(2017)
IEEE Trans. Image Process.
, vol.26
, pp. 4509-4522
-
-
Jin, K.H.1
McCann, M.T.2
Froustey, E.3
Unser, M.4
-
39
-
-
85029824792
-
-
Y. Rivenson, Y. Zhang, H. Gunaydin, D. Teng, and A. Ozcan, “Phase recovery and holographic image reconstruction using deep learning in neural networks,” arXiv:1705.04286 (2017).
-
(2017)
Phase Recovery and Holographic Image Reconstruction Using Deep Learning in Neural Networks
-
-
Rivenson, Y.1
Zhang, Y.2
Gunaydin, H.3
Teng, D.4
Ozcan, A.5
-
40
-
-
85029880593
-
-
Y. Rivenson, Z. Gorocs, H. Gunaydin, Y. Zhang, H. Wang, and A. Ozcan, “Deep learning microscopy,” arXiv:1705.04709 (2017).
-
(2017)
Deep Learning Microscopy
-
-
Rivenson, Y.1
Gorocs, Z.2
Gunaydin, H.3
Zhang, Y.4
Wang, H.5
Ozcan, A.6
-
42
-
-
84947041871
-
Imagenet large scale visual recognition challenge
-
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, and M. Bernstein, “Imagenet large scale visual recognition challenge,” Int. J. Comput. Vis. 115, 211–252 (2015).
-
(2015)
Int. J. Comput. Vis.
, vol.115
, pp. 211-252
-
-
Russakovsky, O.1
Deng, J.2
Su, H.3
Krause, J.4
Satheesh, S.5
Ma, S.6
Huang, Z.7
Karpathy, A.8
Khosla, A.9
Bernstein, M.10
-
43
-
-
51849117118
-
Labeled faces in the wild: A database for studying face recognition in unconstrained environments
-
University of Massachusetts
-
G. B. Huang, M. Ramesh, T. Berg, and E. Learned-Miller, “Labeled faces in the wild: a database for studying face recognition in unconstrained environments,” Technical Report (University of Massachusetts, 2007).
-
(2007)
Technical Report
-
-
Huang, G.B.1
Ramesh, M.2
Berg, T.3
Learned-Miller, E.4
-
45
-
-
77956002520
-
Learning multiple layers of features from tiny images
-
University of Toronto
-
A. Krizhevsky and G. Hinton, “Learning multiple layers of features from tiny images,” Technical Report (University of Toronto, 2009).
-
(2009)
Technical Report
-
-
Krizhevsky, A.1
Hinton, G.2
-
46
-
-
0042357566
-
-
“AT&T database of faces,” Technical Report (AT&T Laboratories Cambridge).
-
Technical Report
-
-
|