-
2
-
-
0025453627
-
Neural network approaches versus statistical methods in classificaion of multisource remote sensing data
-
A. Benediktsson, P. Swain, and O. Ersoy. Neural network approaches versus statistical methods in classificaion of multisource remote sensing data. IEEE Transactions on Geoscience and Remote Sensing, 28(4):550, 1990.
-
(1990)
IEEE Transactions on Geoscience and Remote Sensing
, vol.28
, Issue.4
, pp. 550
-
-
Benediktsson, A.1
Swain, P.2
Ersoy, O.3
-
4
-
-
80052338576
-
Application of multiple-instance learning for hyperspectral image analysis
-
IEEE, : sept
-
J. Bolton and P. Gader. Application of multiple-instance learning for hyperspectral image analysis. Geoscience and Remote Sensing Letters, IEEE, 8(5):889 -893, sept. 2011.
-
(2011)
Geoscience and Remote Sensing Letters
, vol.8
, Issue.5
, pp. 889-893
-
-
Bolton, J.1
Gader, P.2
-
5
-
-
0030618061
-
Multisource classification of complex rural areas by statistical and neural-network approaches
-
May
-
L. Bruzzone, C. Consese, F. Masellit, and F. Roli. Multisource classification of complex rural areas by statistical and neural-network approaches. Photogrammetric Engineering & Remote Sensing, 63(5):523-533, May 1997.
-
(1997)
Photogrammetric Engineering & Remote Sensing
, vol.63
, Issue.5
, pp. 523-533
-
-
Bruzzone, L.1
Consese, C.2
Masellit, F.3
Roli, F.4
-
6
-
-
79958264124
-
Scalable time series change detection for biomass monitoring using Gaussian process
-
V. Chandola and R. R. Vatsavai. Scalable time series change detection for biomass monitoring using gaussian process. In CIDU, pages 69-82, 2010.
-
(2010)
CIDU
, pp. 69-82
-
-
Chandola, V.1
Vatsavai, R.R.2
-
7
-
-
79960363460
-
A scalable Gaussian process analysis algorithm for biomass monitoring
-
V. Chandola and R. R. Vatsavai. A scalable gaussian process analysis algorithm for biomass monitoring. Statistical Analysis and Data Mining, 4(4):430-445, 2011.
-
(2011)
Statistical Analysis and Data Mining
, vol.4
, Issue.4
, pp. 430-445
-
-
Chandola, V.1
Vatsavai, R.R.2
-
8
-
-
0030649484
-
Solving the multiple-instance problem with axis-parallel rectangles
-
T. G. Dietterich, R. H. Lathrop, T. Lozano-Perez, and A. Pharmaceutical. Solving the multiple-instance problem with axis-parallel rectangles. Artificial Intelligence, 89:31-71, 1997.
-
(1997)
Artificial Intelligence
, vol.89
, pp. 31-71
-
-
Dietterich, T.G.1
Lathrop, R.H.2
Lozano-Perez, T.3
Pharmaceutical, A.4
-
9
-
-
0043126911
-
Logistic regression and artificial neural network classification models: A methodology review
-
S. Dreiseitl and L. Ohno-Machado. Logistic regression and artificial neural network classification models: A methodology review. Journal of Biomedical Informatics, 35(5-6):352 - 359, 2002.
-
(2002)
Journal of Biomedical Informatics
, vol.35
, Issue.5-6
, pp. 352-359
-
-
Dreiseitl, S.1
Ohno-Machado, L.2
-
10
-
-
84864741147
-
Image based characterization of formal and informal neighborhoods in an urban landscape. Selected topics in applied earth observations and remote sensing
-
aug
-
J. Graesser, A. Cheriyadat, R. Vatsavai, V. Chandola, J. Long, and E. Bright. Image based characterization of formal and informal neighborhoods in an urban landscape. Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of, 5(4):1164 -1176, aug. 2012.
-
(2012)
IEEE Journal of
, vol.5
, Issue.4
, pp. 1164-1176
-
-
Graesser, J.1
Cheriyadat, A.2
Vatsavai, R.3
Chandola, V.4
Long, J.5
Bright, E.6
-
11
-
-
14644421528
-
Investigation of the random forest framework for classification of hyperspectral data
-
Mar
-
J. Ham, Y. Chen, M. M. Crawford, and J. Ghosh. Investigation of the random forest framework for classification of hyperspectral data. Geoscience and Remote Sensing, IEEE Transactions on, 43(3):492 - 501, Mar. 2005.
-
(2005)
Geoscience and Remote Sensing, IEEE Transactions on
, vol.43
, Issue.3
, pp. 492-501
-
-
Ham, J.1
Chen, Y.2
Crawford, M.M.3
Ghosh, J.4
-
12
-
-
0031106314
-
Strategies and best practice for neural network image classification
-
I. Kanellopoulos and G. G. Wilkinson. Strategies and best practice for neural network image classification. International Journal of Remote Sensing, 18(4):711-725, 1997.
-
(1997)
International Journal of Remote Sensing
, vol.18
, Issue.4
, pp. 711-725
-
-
Kanellopoulos, I.1
Wilkinson, G.G.2
-
13
-
-
21244437589
-
Sparse multinomial logistic regression: Fast algorithms and generalization bounds. Pattern analysis and machine intelligence
-
June
-
B. Krishnapuram, L. Carin, M. A. Figueiredo, and A. J. Hartemink. Sparse multinomial logistic regression: fast algorithms and generalization bounds. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 27(6):957 -968, June 2005.
-
(2005)
IEEE Transactions on
, vol.27
, Issue.6
, pp. 957-968
-
-
Krishnapuram, B.1
Carin, L.2
Figueiredo, M.A.3
Hartemink, A.J.4
-
16
-
-
0029341018
-
A detailed comparison of backpropagation neural network and maximum likelihood classifiers for urban land use classification
-
J. Paola and R. Schowengerdt. A detailed comparison of backpropagation neural network and maximum likelihood classifiers for urban land use classification. IEEE Transactions on Geoscience and Remote Sensing, 33(4):981-996, 1995.
-
(1995)
IEEE Transactions on Geoscience and Remote Sensing
, vol.33
, Issue.4
, pp. 981-996
-
-
Paola, J.1
Schowengerdt, R.2
-
17
-
-
0030618062
-
The effect of neural-network structure on a multispectral land-use/land-cover classification
-
J. Paola and R. Schowengerdt. The effect of neural-network structure on a multispectral land-use/land-cover classification. Photogrammetric Engineering & Remote Sensing, 63(5):535-544, 1997.
-
(1997)
Photogrammetric Engineering & Remote Sensing
, vol.63
, Issue.5
, pp. 535-544
-
-
Paola, J.1
Schowengerdt, R.2
-
18
-
-
0036613147
-
Spatial contextual classification and prediction models for mining geospatial data
-
S. Shekhar, P. Schrater, R. Vatsavai, W. Wu, and S. Chawla. Spatial contextual classification and prediction models for mining geospatial data. IEEE Transaction on Multimedia, 4(2):174-188, 2002.
-
(2002)
IEEE Transaction on Multimedia
, vol.4
, Issue.2
, pp. 174-188
-
-
Shekhar, S.1
Schrater, P.2
Vatsavai, R.3
Wu, W.4
Chawla, S.5
-
19
-
-
0030613489
-
Performance of a neural network: Mapping forest using gis and remorely sensed data
-
May
-
A. Skidmore, B. Turner, W. Brinkhof, and E. Knowles. Performance of a neural network: Mapping forest using gis and remorely sensed data. Photogrammetric Engineering & Remote Sensing, 63(5):501-514, May 1997.
-
(1997)
Photogrammetric Engineering & Remote Sensing
, vol.63
, Issue.5
, pp. 501-514
-
-
Skidmore, A.1
Turner, B.2
Brinkhof, W.3
Knowles, E.4
-
20
-
-
72049131318
-
Multiple instance and context dependent learning in hyperspectral data. In hyperspectral image and signal Processing: Evolution in remote sensing, 2009
-
aug
-
P. Torrione, C. Ratto, and L. Collins. Multiple instance and context dependent learning in hyperspectral data. In Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2009. WHISPERS '09. First Workshop on, pages 1 -4, aug. 2009.
-
(2009)
WHISPERS '09. First Workshop, on
, pp. 1-4
-
-
Torrione, P.1
Ratto, C.2
Collins, L.3
-
21
-
-
84857153519
-
High-resolution urban image classification using extended features
-
R. R. Vatsavai. High-resolution urban image classification using extended features. In ICDM Workshops, pages 869-876, 2011.
-
(2011)
ICDM Workshops
, pp. 869-876
-
-
Vatsavai, R.R.1
-
22
-
-
84873125440
-
A data mining framework for monitoring nuclear facilities
-
Industry/Government Track
-
R. R. Vatsavai. A data mining framework for monitoring nuclear facilities. In ICDM Workshops (Industry/Government Track), page 917, 2012.
-
(2012)
ICDM Workshops
, pp. 917
-
-
Vatsavai, R.R.1
-
24
-
-
78650866045
-
Geospatial image mining for nuclear proliferation detection: Challenges and new opportunities
-
R. R. Vatsavai, B. L. Bhaduri, A. Cheriyadat, L. F. Arrowood, E. A. Bright, S. S. Gleason, C. Diegert, A. K. Katsaggelos, T. Pappas, R. Porter, J. Bollinger, B. Chen, and R. Hohimer. Geospatial image mining for nuclear proliferation detection: Challenges and new opportunities. In IGARSS, pages 48-51, 2010.
-
(2010)
IGARSS
, pp. 48-51
-
-
Vatsavai, R.R.1
Bhaduri, B.L.2
Cheriyadat, A.3
Arrowood, L.F.4
Bright, E.A.5
Gleason, S.S.6
Diegert, C.7
Katsaggelos, A.K.8
Pappas, T.9
Porter, R.10
Bollinger, J.11
Chen, B.12
Hohimer, R.13
-
25
-
-
79960089324
-
Machine learning approaches for high-resolution urban land cover classification: A comparative study
-
R. R. Vatsavai, E. A. Bright, V. Chandola, B. L. Bhaduri, A. Cheriyadat, and J. Graesser. Machine learning approaches for high-resolution urban land cover classification: A comparative study. In COM.Geo, page 11, 2011.
-
(2011)
COM.Geo
, pp. 11
-
-
Vatsavai, R.R.1
Bright, E.A.2
Chandola, V.3
Bhaduri, B.L.4
Cheriyadat, A.5
Graesser, J.6
-
26
-
-
0141596676
-
Solving the multiple-instance problem: A lazy learning approach
-
Morgan Kaufmann
-
J. Wang. Solving the multiple-instance problem: A lazy learning approach. In Proc. 17th International Conf. on Machine Learning, pages 1119-1125. Morgan Kaufmann, 2000.
-
(2000)
Proc. 17th International Conf. on Machine Learning
, pp. 1119-1125
-
-
Wang, J.1
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