-
1
-
-
33745433012
-
Smart cities: Quality of life, productivity, and the growth effects of human capital
-
J. M. Shapiro, "Smart cities: Quality of life, productivity, and the growth effects of human capital, " Rev. Econ. Stat., vol. 88, no. 2, pp. 324-335, 2006.
-
(2006)
Rev. Econ. Stat.
, vol.88
, Issue.2
, pp. 324-335
-
-
Shapiro, J.M.1
-
2
-
-
84874548105
-
Human settlements: A global challenge for EO data processing and interpretation
-
Mar
-
P. Gamba, "Human settlements: A global challenge for EO data processing and interpretation, " Proc. IEEE, vol. 101, no. 3, pp. 570-581, Mar. 2013.
-
(2013)
Proc. IEEE
, vol.101
, Issue.3
, pp. 570-581
-
-
Gamba, P.1
-
3
-
-
66249130979
-
Automated hyperspectral cueing for civilian search and rescue
-
Jun
-
M. T. Eismann, A. D. Stocker, and N. M. Nasrabadi, "Automated hyperspectral cueing for civilian search and rescue, " Proc. IEEE, vol. 97, no. 6, pp. 1031-1055, Jun. 2009.
-
(2009)
Proc. IEEE
, vol.97
, Issue.6
, pp. 1031-1055
-
-
Eismann, M.T.1
Stocker, A.D.2
Nasrabadi, N.M.3
-
4
-
-
84866550700
-
Information extraction from remote sensing images for flood monitoring and damage evaluation
-
Oct
-
S. B. Serpico, S. Dellepiane, G. Boni, G. Moser, E. Angiati, and R. Rudari, "Information extraction from remote sensing images for flood monitoring and damage evaluation, " Proc. IEEE, vol. 100, no. 10, pp. 2946-2970, Oct. 2012.
-
(2012)
Proc. IEEE
, vol.100
, Issue.10
, pp. 2946-2970
-
-
Serpico, S.B.1
Dellepiane, S.2
Boni, G.3
Moser, G.4
Angiati, E.5
Rudari, R.6
-
6
-
-
84953314366
-
Using twitter for tasking remote-sensing data collection and damage assessment: 2013 Boulder flood case study
-
Dec
-
G. Cervone, E. Sava, Q. Huang, E. Schnebele, J. Harrison, and N. Waters, "Using twitter for tasking remote-sensing data collection and damage assessment: 2013 Boulder flood case study, " Int. J. Remote Sens., vol. 37, no. 1, pp. 100-124, Dec. 2015.
-
(2015)
Int. J. Remote Sens.
, vol.37
, Issue.1
, pp. 100-124
-
-
Cervone, G.1
Sava, E.2
Huang, Q.3
Schnebele, E.4
Harrison, J.5
Waters, N.6
-
7
-
-
84856005946
-
Crowdsourcing earthquake damage assessment using remote sensing imagery
-
L. Barrington, S. Ghosh, M. Greene, and S. Harnoy, "Crowdsourcing earthquake damage assessment using remote sensing imagery, " Ann. Geophys., vol. 54, no. 6, pp. 680-687, 2011.
-
(2011)
Ann. Geophys.
, vol.54
, Issue.6
, pp. 680-687
-
-
Barrington, L.1
Ghosh, S.2
Greene, M.3
Harnoy, S.4
-
8
-
-
84939794631
-
Computational approaches for urban environments
-
New York, NY, USA: Springer-Verlag ch. 14
-
E. Schnebele, C. Oxendine, G. Cervone, C. M. Ferreira, and N. Waters, "Computational approaches for urban environments, " in Using Non-Authoritative Sources During Emergencies in Urban Areas. New York, NY, USA: Springer-Verlag, 2015, pp. 337-361, ch. 14.
-
(2015)
Using Non-Authoritative Sources during Emergencies in Urban Areas
, pp. 337-361
-
-
Schnebele, E.1
Oxendine, C.2
Cervone, G.3
Ferreira, C.M.4
Waters, N.5
-
9
-
-
84949180077
-
-
New York, NY, USA: Springer-Verlag
-
C. Aggarwal and T. Abdelzaher, Managing and Mining Sensor Data. New York, NY, USA: Springer-Verlag, 2013, pp. 237-275.
-
(2013)
Managing and Mining Sensor Data
, pp. 237-275
-
-
Aggarwal, C.1
Abdelzaher, T.2
-
10
-
-
81355138524
-
Mobile crowdsensing: Current state and future challenges
-
Nov
-
R. Ganti, F. Ye, and H. Lei, "Mobile crowdsensing: Current state and future challenges, " IEEE Commun. Mag., vol. 49, no. 11, pp. 32-39, Nov. 2011.
-
(2011)
IEEE Commun. Mag.
, vol.49
, Issue.11
, pp. 32-39
-
-
Ganti, R.1
Ye, F.2
Lei, H.3
-
12
-
-
84994297166
-
Big data for remote sensing: Challenges and opportunities
-
Nov
-
M. Chi, A. Plaza, J. A. Benediktsson, Z. Sun, J. Sheng, and Y. Zhu, "Big data for remote sensing: Challenges and opportunities, " Proc. IEEE, vol. 104, no. 11, pp. 2207-2219, Nov. 2016.
-
(2016)
Proc. IEEE
, vol.104
, Issue.11
, pp. 2207-2219
-
-
Chi, M.1
Plaza, A.2
Benediktsson, J.A.3
Sun, Z.4
Sheng, J.5
Zhu, Y.6
-
13
-
-
84973908877
-
Aggregating deep convolutional features for image retrieval
-
Oct
-
A. Babenko and V. Lempitsky, "Aggregating deep convolutional features for image retrieval, " CoRR, Oct. 2015.
-
(2015)
CoRR
-
-
Babenko, A.1
Lempitsky, V.2
-
14
-
-
84933585162
-
Very deep convolutional networks for large-scale image recognition
-
Sep
-
K. Simonyan and A. Zisserman, "Very deep convolutional networks for large-scale image recognition, " CoRR, Sep. 2014.
-
(2014)
CoRR
-
-
Simonyan, K.1
Zisserman, A.2
-
15
-
-
0000359337
-
Backpropagation applied to handwritten zip code recognition
-
Y. LeCun et al., "Backpropagation applied to handwritten zip code recognition, " Neural Comput., vol. 1, no. 4, pp. 541-551, 1989.
-
(1989)
Neural Comput.
, vol.1
, Issue.4
, pp. 541-551
-
-
LeCun, Y.1
-
16
-
-
84876231242
-
Imagenet classification with deep convolutional neural networks
-
A. Krizhevsky, I. Sutskever, and G. E. Hinton, "Imagenet classification with deep convolutional neural networks, " in Proc. 25th Int. Conf. Neural Inf. Process. Syst. (NIPS), 2012, pp. 1097-1105.
-
(2012)
Proc. 25th Int. Conf. Neural Inf. Process. Syst. (NIPS)
, pp. 1097-1105
-
-
Krizhevsky, A.1
Sutskever, I.2
Hinton, G.E.3
-
17
-
-
0029679131
-
Active learning with statistical models
-
Mar
-
D. A. Cohn, Z. Ghahramani, and M. I. Jordan, "Active learning with statistical models, " J. Artif. Intell. Res., vol. 4, pp. 129-145, Mar. 1996.
-
(1996)
J. Artif. Intell. Res.
, vol.4
, pp. 129-145
-
-
Cohn, D.A.1
Ghahramani, Z.2
Jordan, M.I.3
-
18
-
-
84874518998
-
Active learning: Any value for classification of remotely sensed data
-
Mar
-
M. M. Crawford, D. Tuia, and H. L. Yang, "Active learning: Any value for classification of remotely sensed data" Proc. IEEE, vol. 101, no. 3, pp. 593-608, Mar. 2013.
-
(2013)
Proc. IEEE
, vol.101
, Issue.3
, pp. 593-608
-
-
Crawford, M.M.1
Tuia, D.2
Yang, H.L.3
-
19
-
-
85039155184
-
Superpixel-based active learning for the classification of hyperspectral images
-
Tokyo, Japan, Jun
-
Z. Sun and M. Chi, "Superpixel-based active learning for the classification of hyperspectral images, " in Proc. 7th Workshop Hyperspectral Image Signal Process., Evol. Remote Sens., Tokyo, Japan, Jun. 2015.
-
(2015)
Proc. 7th Workshop Hyperspectral Image Signal Process., Evol. Remote Sens.
-
-
Sun, Z.1
Chi, M.2
-
20
-
-
34249810956
-
Semisupervised classification of hyperspectral images by SVMs optimized in the primal
-
Jun
-
M. Chi and L. Bruzzone, "Semisupervised classification of hyperspectral images by SVMs optimized in the primal, " IEEE Trans. Geosci. Remote Sens., vol. 45, no. 6, pp. 1870-1880, Jun. 2007.
-
(2007)
IEEE Trans. Geosci. Remote Sens.
, vol.45
, Issue.6
, pp. 1870-1880
-
-
Chi, M.1
Bruzzone, L.2
-
21
-
-
33749252873
-
-
Cambridge, MA, USA: MIT Press
-
O. Chapelle, B. Schölkopf, and A. Zien, Eds., Semi-Supervised Learning. Cambridge, MA, USA: MIT Press, 2006.
-
(2006)
Semi-Supervised Learning
-
-
Chapelle, O.1
Schölkopf, B.2
Zien, A.3
-
22
-
-
33745456231
-
-
Ph. D. dissertation, Dept. Comput. Sci., Univ. Wisconsin, Madison, WI, USA
-
X. Zhu, "Semi-supervised learning literature survey, " Ph. D. dissertation, Dept. Comput. Sci., Univ. Wisconsin, Madison, WI, USA, 2008.
-
(2008)
Semi-supervised Learning Literature Survey
-
-
Zhu, X.1
-
23
-
-
0042868698
-
Support vector machine active learning with applications to text classification
-
Mar
-
S. Tong and D. Koller, "Support vector machine active learning with applications to text classification, " J. Mach. Learn. Res., vol. 2, pp. 45-66, Mar. 2001.
-
(2001)
J. Mach. Learn. Res.
, vol.2
, pp. 45-66
-
-
Tong, S.1
Koller, D.2
-
24
-
-
80053375448
-
An analysis of active learning strategies for sequence labeling tasks
-
Stroudsburg, PA, USA
-
B. Settles and M. Craven, "An analysis of active learning strategies for sequence labeling tasks, " in Proc. Conf. Empirical Methods Natural Lang. Process. (EMNLP), Stroudsburg, PA, USA, 2008, pp. 1070-1079.
-
(2008)
Proc. Conf. Empirical Methods Natural Lang. Process. (EMNLP)
, pp. 1070-1079
-
-
Settles, B.1
Craven, M.2
-
25
-
-
84866702739
-
Scalable active learning for multiclass image classification
-
Nov
-
A. J. Joshi, P. Fatih, and N. P. Papanikolopoulos, "Scalable active learning for multiclass image classification, " IEEE Trans. Softw. Eng., vol. 34, no. 11, pp. 2259-2273, Nov. 2012.
-
(2012)
IEEE Trans. Softw. Eng.
, vol.34
, Issue.11
, pp. 2259-2273
-
-
Joshi, A.J.1
Fatih, P.2
Papanikolopoulos, N.P.3
-
26
-
-
0000710299
-
Queries and concept learning
-
D. Angluin, "Queries and concept learning, " Mach. Learn., vol. 2, no. 4, pp. 319-342, 1987.
-
(1987)
Mach. Learn.
, vol.2
, Issue.4
, pp. 319-342
-
-
Angluin, D.1
-
27
-
-
0028424239
-
Improving generalization with active learning
-
D. Cohn, L. Atlas, and R. Ladner, "Improving generalization with active learning, " Mach. Learn., vol. 15, no. 2, pp. 201-221, 1996.
-
(1996)
Mach. Learn.
, vol.15
, Issue.2
, pp. 201-221
-
-
Cohn, D.1
Atlas, L.2
Ladner, R.3
-
29
-
-
79957456032
-
A survey of active learning algorithms for supervised remote sensing image classification
-
Jun
-
D. Tuia, M. Volpi, L. Copa, M. Kanevski, and J. Munoz-Mari, "A survey of active learning algorithms for supervised remote sensing image classification, " IEEE J. Sel. Topics Signal Process., vol. 5, no. 3, pp. 606-617, Jun. 2011.
-
(2011)
IEEE J. Sel. Topics Signal Process.
, vol.5
, Issue.3
, pp. 606-617
-
-
Tuia, D.1
Volpi, M.2
Copa, L.3
Kanevski, M.4
Munoz-Mari, J.5
-
30
-
-
84874518998
-
Active learning: Any value for classification of remotely sensed data
-
Mar
-
M. M. Crawford, D. Tuia, and H. L. Yang, "Active learning: Any value for classification of remotely sensed data" Proc. IEEE, vol. 100, no. 3, pp. 593-608, Mar. 2013.
-
(2013)
Proc. IEEE
, vol.100
, Issue.3
, pp. 593-608
-
-
Crawford, M.M.1
Tuia, D.2
Yang, H.L.3
-
31
-
-
68949137209
-
-
Dept. Comput. Sci., Univ. Wisconsin, Madison, WI, USA, Tech. Rep., 1648, Jan
-
B. Settles, "Active learning literature survey, " Dept. Comput. Sci., Univ. Wisconsin, Madison, WI, USA, Tech. Rep., 1648, Jan. 2010.
-
(2010)
Active Learning Literature Survey
-
-
Settles, B.1
-
32
-
-
0038399423
-
Query learning with large margin classifiers
-
San Francisco, CA, USA
-
C. Campbell, N. Cristianini, and A. J. Smola, "Query learning with large margin classifiers, " in Proc. 17th Int. Conf. Mach. Learn., San Francisco, CA, USA, 2000, pp. 111-118.
-
(2000)
Proc. 17th Int. Conf. Mach. Learn.
, pp. 111-118
-
-
Campbell, C.1
Cristianini, N.2
Smola, A.J.3
-
33
-
-
40149096977
-
A stopping criterion for active learning
-
A. Vlachos, "A stopping criterion for active learning, " Comput. Speech Lang., vol. 22, no. 3, pp. 295-312, 2008.
-
(2008)
Comput. Speech Lang.
, vol.22
, Issue.3
, pp. 295-312
-
-
Vlachos, A.1
-
34
-
-
79952041537
-
Batch-mode active-learning methods for the interactive classification of remote sensing images
-
Mar
-
B. Demir, C. Persello, and L. Bruzzone, "Batch-mode active-learning methods for the interactive classification of remote sensing images, " IEEE Trans. Geosci. Remote Sens., vol. 49, no. 3, pp. 1014-1031, Mar. 2011.
-
(2011)
IEEE Trans. Geosci. Remote Sens.
, vol.49
, Issue.3
, pp. 1014-1031
-
-
Demir, B.1
Persello, C.2
Bruzzone, L.3
-
35
-
-
34249753618
-
Support-vector networks
-
C. Cortes and V. Vapnik, "Support-vector networks, " Mach. Learn., vol. 20, no. 3, pp. 273-297, 1995.
-
(1995)
Mach. Learn.
, vol.20
, Issue.3
, pp. 273-297
-
-
Cortes, C.1
Vapnik, V.2
-
36
-
-
85039155184
-
Superpixel-based active learning for the classification of hyperspectral images
-
Tokyo, Japan, Jun
-
Z. Sun and M. Chi, "Superpixel-based active learning for the classification of hyperspectral images, " in Proc. 7th Workshop Hyperspectral Image Signal Process., Evol. Remote Sens., Tokyo, Japan, Jun. 2015, pp. 1-41.
-
(2015)
Proc. 7th Workshop Hyperspectral Image Signal Process., Evol. Remote Sens.
, pp. 1-41
-
-
Sun, Z.1
Chi, M.2
-
37
-
-
33847246935
-
The rise of crowdsourcing
-
Jun
-
J. Howe, "The rise of crowdsourcing, " Wired Mag., vol. 14, no. 6, pp. 1-4, Jun. 2006.
-
(2006)
Wired Mag.
, vol.14
, Issue.6
, pp. 1-4
-
-
Howe, J.1
-
38
-
-
45949105508
-
Crowdsourcing as a model for problem solving: An introduction and cases
-
D. C. Brabham, "Crowdsourcing as a model for problem solving: An introduction and cases, " Converg., Int. J. Res. Into New Media Technol., vol. 14, no. 1, pp. 75-90, 2008.
-
(2008)
Converg., Int. J. Res. into New Media Technol.
, vol.14
, Issue.1
, pp. 75-90
-
-
Brabham, D.C.1
-
39
-
-
85198028989
-
ImageNet: A large-scale hierarchical image database
-
Jun
-
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei, "ImageNet: A large-scale hierarchical image database, " in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), Jun. 2009, pp. 248-255.
-
(2009)
Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR)
, pp. 248-255
-
-
Deng, J.1
Dong, W.2
Socher, R.3
Li, L.-J.4
Li, K.5
Fei-Fei, L.6
-
40
-
-
85030086742
-
-
Amazon Turkey Market. [Online]. Available: https://www. mturk. com/mturk/welcome
-
Amazon Turkey Market
-
-
-
41
-
-
84947041871
-
ImageNet large scale visual recognition challenge
-
Dec
-
O. Russakovsky et al., "ImageNet large scale visual recognition challenge, " Int. J. Comput. Vis., vol. 115, no. 3, pp. 211-252, Dec. 2015.
-
(2015)
Int. J. Comput. Vis.
, vol.115
, Issue.3
, pp. 211-252
-
-
Russakovsky, O.1
-
43
-
-
33745805403
-
A fast learning algorithm for deep belief nets
-
G. E. Hinton, S. Osindero, and Y.-W. Teh, "A fast learning algorithm for deep belief nets, " Neural Comput., vol. 18, no. 7, pp. 1527-1554, 2006.
-
(2006)
Neural Comput.
, vol.18
, Issue.7
, pp. 1527-1554
-
-
Hinton, G.E.1
Osindero, S.2
Teh, Y.-W.3
-
44
-
-
84883366075
-
Active learning and crowd-sourcing for machine translation
-
Valletta, Malta, May
-
V. Ambati, S. Vogel, and J. Carbonell, "Active learning and crowd-sourcing for machine translation, " in Proc. 7th Int. Conf. Lang. Resour. Eval. (LREC), Valletta, Malta, May 2010, pp. 2169-2174.
-
(2010)
Proc. 7th Int. Conf. Lang. Resour. Eval. (LREC)
, pp. 2169-2174
-
-
Ambati, V.1
Vogel, S.2
Carbonell, J.3
-
45
-
-
84857558347
-
On using crowdsourcing and active learning to improve classification performance
-
Cordoba, Spain
-
J. Costa, C. Silva, M. Antunes, and B. Ribeiro, "On using crowdsourcing and active learning to improve classification performance, " in Proc. 11th Int. Conf. Intell. Syst. Des. Appl. (ISDA), Cordoba, Spain, 2011, pp. 469-474.
-
(2011)
Proc. 11th Int. Conf. Intell. Syst. Des. Appl. (ISDA)
, pp. 469-474
-
-
Costa, J.1
Silva, C.2
Antunes, M.3
Ribeiro, B.4
-
46
-
-
77956050042
-
Using crowdsourcing and active learning to track sentiment in online media
-
Amsterdam, The Netherlands
-
A. Brew, D. Greene, and P. Cunningham, "Using crowdsourcing and active learning to track sentiment in online media, " in Proc. 19th Eur. Conf. Artif. Intell. Conf. (ECAI), Amsterdam, The Netherlands, 2010, pp. 145-150.
-
(2010)
Proc. 19th Eur. Conf. Artif. Intell. Conf. (ECAI)
, pp. 145-150
-
-
Brew, A.1
Greene, D.2
Cunningham, P.3
-
47
-
-
84875749706
-
Quality control in crowdsourcing systems: Issues and directions
-
Mar
-
M. Allahbakhsh, B. Benatallah, A. Ignjatovic, H. R. Motahari-Nezhad, E. Bertino, and S. Dustdar, "Quality control in crowdsourcing systems: Issues and directions, " IEEE Internet Comput., vol. 17, no. 2, pp. 76-81, Mar. 2013.
-
(2013)
IEEE Internet Comput.
, vol.17
, Issue.2
, pp. 76-81
-
-
Allahbakhsh, M.1
Benatallah, B.2
Ignjatovic, A.3
Motahari-Nezhad, H.R.4
Bertino, E.5
Dustdar, S.6
-
48
-
-
80055052639
-
On quality control and machine learning in crowdsourcing
-
M. Lease, "On quality control and machine learning in crowdsourcing, " in Proc. 11th AAAI Conf. Human Comput. (AAAIWS), 2011, pp. 97-102.
-
(2011)
Proc. 11th AAAI Conf. Human Comput. (AAAIWS)
, pp. 97-102
-
-
Lease, M.1
-
49
-
-
80054081629
-
Quality control for real-time ubiquitous crowdsourcing
-
New York, NY, USA
-
Mashhadi and L. Capra, "Quality control for real-time ubiquitous crowdsourcing, " in Proc. 2nd Int. Workshop Ubiquitous Crowdsouring (UbiCrowd), New York, NY, USA, 2011, pp. 5-8.
-
(2011)
Proc. 2nd Int. Workshop Ubiquitous Crowdsouring (UbiCrowd)
, pp. 5-8
-
-
Mashhadi1
Capra, L.2
-
50
-
-
0036647190
-
An efficient k-means clustering algorithm: Analysis and implementation
-
Jul
-
T. Kanungo, D. M. Mount, N. S. Netanyahu, C. D. Piatko, R. Silverman, and A. Y. Wu, "An efficient k-means clustering algorithm: Analysis and implementation, " IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 7, pp. 881-892, Jul. 2002.
-
(2002)
IEEE Trans. Pattern Anal. Mach. Intell.
, vol.24
, Issue.7
, pp. 881-892
-
-
Kanungo, T.1
Mount, D.M.2
Netanyahu, N.S.3
Piatko, C.D.4
Silverman, R.5
Wu, A.Y.6
-
51
-
-
33749264994
-
A survey of content-based image retrieval with high-level semantics
-
Y. Liu, D. Zhang, G. Lu, and W.-Y. Ma, "A survey of content-based image retrieval with high-level semantics, " Pattern Recognit., vol. 40, no. 1, pp. 262-282, 2007.
-
(2007)
Pattern Recognit.
, vol.40
, Issue.1
, pp. 262-282
-
-
Liu, Y.1
Zhang, D.2
Lu, G.3
Ma, W.-Y.4
-
52
-
-
0033284915
-
Object recognition from local scale-invariant features
-
Kerkyra, Greece, Sep
-
D. G. Lowe, "Object recognition from local scale-invariant features, " in Proc. Int. Conf. Comput. Vis., Kerkyra, Greece, Sep. 1999, pp. 1150-1159.
-
(1999)
Proc. Int. Conf. Comput. Vis.
, pp. 1150-1159
-
-
Lowe, D.G.1
-
54
-
-
77956004473
-
Aggregating local descriptors into a compact image representation
-
H. Jégou, M. Douze, C. Schmid, and P. Pérez, "Aggregating local descriptors into a compact image representation, " in Proc. CVPR, Jun. 2010, vol. 238. no. 6, pp. 3304-3311.
-
(2010)
Proc. CVPR, Jun
, vol.238
, Issue.6
, pp. 3304-3311
-
-
Jégou, H.1
Douze, M.2
Schmid, C.3
Pérez, P.4
-
55
-
-
79959771606
-
Improving the fisher kernel for large-scale image classification
-
Heraklion, Greece, Sep
-
F. Perronnin, J. Sánchez, and T. Mensink, "Improving the fisher kernel for large-scale image classification, " in Proc. Eur. Conf. Comput. Vis. (ECCV), Heraklion, Greece, Sep. 2010, pp. 119-133.
-
(2010)
Proc. Eur. Conf. Comput. Vis. (ECCV)
, pp. 119-133
-
-
Perronnin, F.1
Sánchez, J.2
Mensink, T.3
-
56
-
-
33645146449
-
Histograms of oriented gradients for human detection
-
San Diego, CA, USA, Jun
-
N. Dalal and B. Triggs, "Histograms of oriented gradients for human detection, " in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit., San Diego, CA, USA, Jun. 2005, pp. 886-893.
-
(2005)
Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit.
, pp. 886-893
-
-
Dalal, N.1
Triggs, B.2
-
57
-
-
84911400494
-
Rich feature hierarchies for accurate object detection and semantic segmentation
-
Washington, DC, USA, Jun
-
R. Girshick, J. Donahue, T. Darrell, and J. Malik, "Rich feature hierarchies for accurate object detection and semantic segmentation, " in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), Washington, DC, USA, Jun. 2014, pp. 580-587.
-
(2014)
Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR)
, pp. 580-587
-
-
Girshick, R.1
Donahue, J.2
Darrell, T.3
Malik, J.4
-
58
-
-
84977618390
-
You only look once: Unified, real-time object detection
-
J. Redmon, S. Divvala, R. Girshick, and A. Farhadi, "You only look once: Unified, real-time object detection, " CoRR, Jun. 2015.
-
(2015)
CoRR, Jun
-
-
Redmon, J.1
Divvala, S.2
Girshick, R.3
Farhadi, A.4
-
59
-
-
84913580146
-
Caffe: Convolutional architecture for fast feature embedding
-
Orlando, FL, USA
-
Y. Jia et al., "Caffe: Convolutional architecture for fast feature embedding, " in Proc. 22nd ACM Int. Conf. Multimedia, Orlando, FL, USA, 2014, pp. 675-678.
-
(2014)
Proc. 22nd ACM Int. Conf. Multimedia
, pp. 675-678
-
-
Jia, Y.1
-
60
-
-
0035478854
-
Random forests
-
L. Breiman, "Random forests, " Mach. Learn., vol. 45, no. 1, pp. 5-32, 2001.
-
(2001)
Mach. Learn.
, vol.45
, Issue.1
, pp. 5-32
-
-
Breiman, L.1
|