-
1
-
-
84913592850
-
-
Qualinet 3 June 2012 (12 December, 2015)
-
Qualinet, "Qualinet white paper on definitions of quality of experience," 3 June 2012, http://www.qualinet.eu/images/stories/whitepaper-v1.1-dagstuhl-output-corrected.pdf (12 December 2015).
-
Qualinet White Paper on Definitions of Quality of Experience
-
-
-
2
-
-
79957780748
-
Objective video quality assessment methods: A classification, review, performance comparison
-
S. Chikkerur et al., "Objective video quality assessment methods: a classification, review, performance comparison," IEEE Trans. Broadcast. 57, 165-182 (2011).
-
(2011)
IEEE Trans. Broadcast.
, vol.57
, pp. 165-182
-
-
Chikkerur, S.1
-
4
-
-
0036650987
-
Objective quality assessment of MPEG-2 video streams by using CBP neural networks
-
P. Gastaldo, S. Rovetta, R. Zunino, "Objective quality assessment of MPEG-2 video streams by using CBP neural networks," IEEE Trans. Neural Netw. 13, 939-947 (2002).
-
(2002)
IEEE Trans. Neural Netw.
, vol.13
, pp. 939-947
-
-
Gastaldo, P.1
Rovetta, S.2
Zunino, R.3
-
5
-
-
33750135479
-
A convolutional neural network approach for objective video quality assessment
-
P. Le Callet, C. Viard-Gaudin, D. Barba, "A convolutional neural network approach for objective video quality assessment," IEEE Trans. Neural Netw. 17, 1316-1327 (2006).
-
(2006)
IEEE Trans. Neural Netw.
, vol.17
, pp. 1316-1327
-
-
Le Callet, P.1
Viard-Gaudin, C.2
Barba, D.3
-
6
-
-
84949926896
-
No-reference video quality assessment via feature learning
-
J. Xu et al., "No-reference video quality assessment via feature learning," in IEEE Int. Conf. on Image Processing, pp. 491-495 (2014).
-
(2014)
IEEE Int. Conf. on Image Processing
, pp. 491-495
-
-
Xu, J.1
-
7
-
-
84926457035
-
No-reference video quality assessment based on artifact measurement, statistical analysis
-
K. Zhu et al., "No-reference video quality assessment based on artifact measurement, statistical analysis," IEEE Trans. Circuits Syst. Video Technol. 25(4), 533-546 (2015).
-
(2015)
IEEE Trans. Circuits Syst. Video Technol.
, vol.25
, Issue.4
, pp. 533-546
-
-
Zhu, K.1
-
8
-
-
84881435260
-
Constructing a no-reference H.264/AVC bitstreambased video quality metric using genetic programming-based symbolic regression
-
N. Staelens et al., "Constructing a no-reference H.264/AVC bitstreambased video quality metric using genetic programming-based symbolic regression," IEEE Trans. Circuits Syst. Video Technol. 23, 1322-1333 (2013).
-
(2013)
IEEE Trans. Circuits Syst. Video Technol.
, vol.23
, pp. 1322-1333
-
-
Staelens, N.1
-
9
-
-
84939489965
-
No-reference video quality assessment using codec analysis
-
J. Sogaard, S. Forchhammer, J. Korhonen, "No-reference video quality assessment using codec analysis," IEEE Trans. Circuits Syst. Video Technol. 25(10), 1637-1650 (2015).
-
(2015)
IEEE Trans. Circuits Syst. Video Technol.
, vol.25
, Issue.10
, pp. 1637-1650
-
-
Sogaard, J.1
Forchhammer, S.2
Korhonen, J.3
-
10
-
-
84897741517
-
A spatiotemporal no-reference video quality assessment model
-
B. Konuk et al., "A spatiotemporal no-reference video quality assessment model," in 20th IEEE Int. Conf. on Image Processing, pp. 54-58 (2013).
-
(2013)
20th IEEE Int. Conf. on Image Processing
, pp. 54-58
-
-
Konuk, B.1
-
11
-
-
84938064691
-
No-reference image, video quality assessment: A classification, review of recent approaches
-
M. Shahid et al., "No-reference image, video quality assessment: a classification, review of recent approaches," EURASIP J. Image Video Process. 2014(1), 40 (2014).
-
(2014)
EURASIP J. Image Video Process.
, vol.2014
, Issue.1
, pp. 40
-
-
Shahid, M.1
-
13
-
-
0036995754
-
A study of real-time packet video quality using random neural networks
-
S. Mohamed, G. Rubino, "A study of real-time packet video quality using random neural networks," IEEE Trans. Circuits Syst. Video Technol. 12, 1071-1083 (2002).
-
(2002)
IEEE Trans. Circuits Syst. Video Technol.
, vol.12
, pp. 1071-1083
-
-
Mohamed, S.1
Rubino, G.2
-
14
-
-
69349090197
-
Learning deep architectures for AI
-
Y. Bengio, "Learning deep architectures for AI," Found. Trends Mach. Learn. 2, 1-127 (2009).
-
(2009)
Found. Trends Mach. Learn.
, vol.2
, pp. 1-127
-
-
Bengio, Y.1
-
15
-
-
84970875649
-
Subjective video quality test: Methodology, database, experience
-
J. P. Garella et al., "Subjective video quality test: methodology, database, experience," in IEEE Int. Symp. on Broadband Multimedia Systems, Broadcasting, pp 1-6 (2015).
-
(2015)
IEEE Int. Symp. on Broadband Multimedia Systems, Broadcasting
, pp. 1-6
-
-
Garella, J.P.1
-
16
-
-
84892462269
-
Accounting for diversity in subjective judgments
-
ACM, New York
-
E. Karapanos, J.-B. Martens, M. Hassenzahl, "Accounting for diversity in subjective judgments," in Proc. of the SIGCHI Conf. on Human Factors in Computing Systems, pp. 639-648, ACM, New York (2009).
-
(2009)
Proc. of the SIGCHI Conf. on Human Factors in Computing Systems
, pp. 639-648
-
-
Karapanos, E.1
Martens, J.-B.2
Hassenzahl, M.3
-
18
-
-
85116185326
-
Automation of subjective video quality measurements
-
ACM
-
J. Joskowicz et al., "Automation of subjective video quality measurements," in Proc. of the Latin America Networking Conf., pp. 7:1-7:5, ACM (2014).
-
(2014)
Proc. of the Latin America Networking Conf.
, pp. 71-75
-
-
Joskowicz, J.1
-
19
-
-
84928471699
-
Suitable methodology in subjective video quality assessment: A resolution dependent paradigm
-
S. Péchard, R. Pépion, P. Le Callet, "Suitable methodology in subjective video quality assessment: a resolution dependent paradigm," in Int. Workshop on Image Media Quality, its Applications, p. 6 (2008).
-
(2008)
Int. Workshop on Image Media Quality, Its Applications
, pp. 6
-
-
Péchard, S.1
Pépion, R.2
Le Callet, P.3
-
20
-
-
84899518748
-
A model for video quality assessment considering packet loss for broadcast digital television coded in H.264
-
J. Joskowicz, R. Sotelo, "A model for video quality assessment considering packet loss for broadcast digital television coded in H.264," Int. J. Digit. Multimed. Broadcast. 2014(5786), 11 (2014).
-
(2014)
Int. J. Digit. Multimed. Broadcast.
, vol.2014
, Issue.5786
, pp. 11
-
-
Joskowicz, J.1
Sotelo, R.2
-
21
-
-
0031996770
-
Image, video compression
-
C. Cramer, E. Gelenbe, P. Gelenbe, "Image, video compression," IEEE Potentials 17, 29-33 (1998).
-
(1998)
IEEE Potentials
, vol.17
, pp. 29-33
-
-
Cramer, C.1
Gelenbe, E.2
Gelenbe, P.3
-
22
-
-
17544389864
-
Survey of random neural network applications
-
H. Bakrcolu, T. Kocąk, "Survey of random neural network applications," Eur. J. Oper. Res. 126(2), 319-330 (2000).
-
(2000)
Eur. J. Oper. Res.
, vol.126
, Issue.2
, pp. 319-330
-
-
Bakrcolu, H.1
Kocąk, T.2
-
23
-
-
0000145931
-
Stability of the random neural network model
-
E. Gelenbe, "Stability of the random neural network model," Neural Comput. 2, 239-247 (1990).
-
(1990)
Neural Comput
, vol.2
, pp. 239-247
-
-
Gelenbe, E.1
-
24
-
-
79952385044
-
Quality of experience estimation using frame loss pattern, video encoding characteristics in DVB-H networks
-
K. Singh, G. Rubino, "Quality of experience estimation using frame loss pattern, video encoding characteristics in DVB-H networks," in 18th Int. Packet Video Workshop, pp. 150-157 (2010).
-
(2010)
18th Int. Packet Video Workshop
, pp. 150-157
-
-
Singh, K.1
Rubino, G.2
-
25
-
-
84860702374
-
Quality of experience estimation for adaptive HTTP/TCP video streaming using H.264/AVC
-
K. Singh, Y. Hadjadj-Aoul, G. Rubino, "Quality of experience estimation for adaptive HTTP/TCP video streaming using H.264/AVC," in IEEE Consumer Communications, Networking Conf., pp. 127-131 (2012).
-
(2012)
IEEE Consumer Communications, Networking Conf.
, pp. 127-131
-
-
Singh, K.1
Hadjadj-Aoul, Y.2
Rubino, G.3
-
27
-
-
84892142922
-
Computer science: The learning machines
-
N. Jones, "Computer science: the learning machines," Nature 505(7482), 146-148 (2014).
-
(2014)
Nature
, vol.505
, Issue.7482
, pp. 146-148
-
-
Jones, N.1
-
28
-
-
84897953259
-
From neural networks to deep learning: Zeroing in on the human brain
-
J. Laserson, "From neural networks to deep learning: zeroing in on the human brain," XRDS 18, 29-34 (2011).
-
(2011)
XRDS
, vol.18
, pp. 29-34
-
-
Laserson, J.1
-
29
-
-
56449110012
-
Classification using discriminative restricted Boltzmann machines
-
ACM, New York
-
H. Larochelle, Y. Bengio, "Classification using discriminative restricted Boltzmann machines," in Proc. of the 25th Int. Conf. on Machine Learning, pp. 536-543, ACM, New York (2008).
-
(2008)
Proc. of the 25th Int. Conf. on Machine Learning
, pp. 536-543
-
-
Larochelle, H.1
Bengio, Y.2
-
30
-
-
34547983260
-
Restricted Boltzmann machines for collaborative filtering
-
ACM, New York
-
R. Salakhutdinov, A. Mnih, G. Hinton, "Restricted Boltzmann machines for collaborative filtering," in Proc. of the 24th Int. Conf. on Machine Learning, pp. 791-798, ACM, New York (2007).
-
(2007)
Proc. of the 24th Int. Conf. on Machine Learning
, pp. 791-798
-
-
Salakhutdinov, R.1
Mnih, A.2
Hinton, G.3
-
31
-
-
84886502372
-
Automatically mapped transfer between reinforcement learning tasks via three-way restricted Boltzmann machines
-
H. Ammar et al., "Automatically mapped transfer between reinforcement learning tasks via three-way restricted Boltzmann machines," Lec. Notes Comput. Sci. 8189, 449-464 (2013).
-
(2013)
Lec. Notes Comput. Sci.
, vol.8189
, pp. 449-464
-
-
Ammar, H.1
-
33
-
-
33749243771
-
The rate adapting Poisson model for information retrieval, object recognition
-
ACM, New York
-
P. V. Gehler, A. D. Holub, M. Welling, "The rate adapting Poisson model for information retrieval, object recognition," in Proc. of the 23rd Int. Conf. on Machine Learning, pp. 337-344, ACM, New York (2006).
-
(2006)
Proc. of the 23rd Int. Conf. on Machine Learning
, pp. 337-344
-
-
Gehler, P.V.1
Holub, A.D.2
Welling, M.3
-
34
-
-
84942648494
-
Factored four way conditional restricted Boltzmann machines for activity recognition
-
D. C. Mocanu et al., "Factored four way conditional restricted Boltzmann machines for activity recognition," Pattern Recognit. Lett. 66, 100-108 (2015).
-
(2015)
Pattern Recognit. Lett.
, vol.66
, pp. 100-108
-
-
Mocanu, D.C.1
-
36
-
-
84942645422
-
Reduced reference image quality assessment via Boltzmann machines
-
D. Mocanu et al., "Reduced reference image quality assessment via Boltzmann machines," in IFIP/IEEE Int. Symp. on Integrated Network Management, pp. 1278-1281 (2015).
-
(2015)
IFIP/IEEE Int. Symp. on Integrated Network Management
, pp. 1278-1281
-
-
Mocanu, D.1
-
37
-
-
84911384028
-
Blind image quality assessment using semi-supervised rectifier networks
-
H. Tang, N. Joshi, A. Kapoor, "Blind image quality assessment using semi-supervised rectifier networks," in IEEE Conf. on Computer Vision, Pattern Recognition, pp. 2877-2884 (2014).
-
(2014)
IEEE Conf. on Computer Vision, Pattern Recognition
, pp. 2877-2884
-
-
Tang, H.1
Joshi, N.2
Kapoor, A.3
-
39
-
-
0000329993
-
Information processing in dynamical systems: Foundations of harmony theory
-
D. E. Rumelhart, J. L. McClelland, PDP Research Group MIT Press, Cambridge, Massachusetts
-
P. Smolensky, "Information processing in dynamical systems: foundations of harmony theory, in Parallel Distributed Processing: Explorations in the Microstructure of Cognition," Vol. 1, D. E. Rumelhart, J. L. McClelland, PDP Research Group, pp. 194-281, MIT Press, Cambridge, Massachusetts (1986).
-
(1986)
Parallel Distributed Processing: Explorations in the Microstructure of Cognition
, vol.1
, pp. 194-281
-
-
Smolensky, P.1
-
40
-
-
33745805403
-
A fast learning algorithm for deep belief nets
-
G. E. Hinton, S. Osindero, Y.-W. Teh, "A fast learning algorithm for deep belief nets," Neural Comput. 18, 1527-1554 (2006).
-
(2006)
Neural Comput
, vol.18
, pp. 1527-1554
-
-
Hinton, G.E.1
Osindero, S.2
Teh, Y.-W.3
-
41
-
-
0022471098
-
Learning representations by back-propagating errors
-
D. Rumelhart, G. Hintont, R. Williams, "Learning representations by back-propagating errors," Nature 323(6088), 533-536 (1986).
-
(1986)
Nature
, vol.323
, Issue.6088
, pp. 533-536
-
-
Rumelhart, D.1
Hintont, G.2
Williams, R.3
-
42
-
-
84872506495
-
A practical guide to training restricted Boltzmann machines
-
G. E. Hinton, "A practical guide to training restricted Boltzmann machines," Lec. Notes Comput. Sci. 7700, 599-619 (2012).
-
(2012)
Lec. Notes Comput. Sci.
, vol.7700
, pp. 599-619
-
-
Hinton, G.E.1
-
44
-
-
80555140075
-
Scikit-learn: Machine learning in Python
-
F. Pedregosa et al., "Scikit-learn: Machine learning in Python," J. Mach. Learn. Res. 12, 2825-2830 (2011).
-
(2011)
J. Mach. Learn. Res.
, vol.12
, pp. 2825-2830
-
-
Pedregosa, F.1
|