-
1
-
-
0037898829
-
An innovative real-time technique for buried object detection
-
Bermani, E., A. Boni, S. Caorsi, and A. Massa, "An innovative real-time technique for buried object detection," IEEE Transactions on Geoscience and Remote Sensing, Vol. 41, No. 4, 927-931, 2003.
-
(2003)
IEEE Transactions on Geoscience and Remote Sensing
, vol.41
, Issue.4
, pp. 927-931
-
-
Bermani, E.1
Boni, A.2
Caorsi, S.3
Massa, A.4
-
2
-
-
0003450542
-
-
Statistics for Engineering and Information Science, 2nd edition, Springer Verlag
-
Vapnik, V. N., The Nature of Statistical Learning Theory, Statistics for Engineering and Information Science, 2nd edition, Springer Verlag, 1999.
-
(1999)
The Nature of Statistical Learning Theory
-
-
Vapnik, V.N.1
-
3
-
-
0041880602
-
A comparative study of nn and svm-based electromagnetic inverse scattering approaches to on-line detection of buried objects
-
Caorsi, S., D. Anguita, E. Bermani, A. Boni, and M. Donelli, "A comparative study of nn and svm-based electromagnetic inverse scattering approaches to on-line detection of buried objects," ACES Journal, Vol. 18, No. 2, 2003.
-
(2003)
ACES Journal
, vol.18
, Issue.2
-
-
Caorsi, S.1
Anguita, D.2
Bermani, E.3
Boni, A.4
Donelli, M.5
-
5
-
-
0004094721
-
-
MIT Press, Cambridge, MA
-
Schölkopf, B. and A. J. Smola, Learning with Kernels, MIT Press, Cambridge, MA, 2002.
-
(2002)
Learning with Kernels
-
-
Schölkopf, B.1
Smola, A.J.2
-
7
-
-
0000874557
-
Theoretical foundations of the potential function method in pattern recognition learning
-
Aizerman, M. A., E. M. Braverman, and L. I. Rozonoer, "Theoretical foundations of the potential function method in pattern recognition learning," Automation and Remote Control, Vol. 25, 821-837, 1964.
-
(1964)
Automation and Remote Control
, vol.25
, pp. 821-837
-
-
Aizerman, M.A.1
Braverman, E.M.2
Rozonoer, L.I.3
-
8
-
-
0003120218
-
Fast training of support vector machines using sequential minimal optimization
-
B. Scölkopf, C. Burges, and A. Smola (Eds.), MIT Press
-
Platt, J., "Fast training of support vector machines using sequential minimal optimization," Advances in Kernel Methods-Support Vector Learning, B. Scölkopf, C. Burges, and A. Smola (Eds.), MIT Press, 1999.
-
(1999)
Advances in Kernel Methods-Support Vector Learning
-
-
Platt, J.1
-
9
-
-
0036129250
-
Asymptotic convergence of an SMO algorithm without any assumptions
-
Jan
-
Lin, C.-J., "Asymptotic convergence of an SMO algorithm without any assumptions," IEEE Trans. on Neural Networks, Vol. 13, No. 1, 248-250, Jan. 2002.
-
(2002)
IEEE Trans. on Neural Networks
, vol.13
, Issue.1
, pp. 248-250
-
-
Lin, C.-J.1
-
10
-
-
17444438778
-
New support vector algorithms
-
May
-
Smola, A., B. Schölkopf, R. Williamson, and P. Bartlett, "New support vector algorithms," Neural Computation, Vol. 12, No. 5, 1207-1245, May 2000.
-
(2000)
Neural Computation
, vol.12
, Issue.5
, pp. 1207-1245
-
-
Smola, A.1
Schölkopf, B.2
Williamson, R.3
Bartlett, P.4
-
12
-
-
0003684449
-
-
Springer, New York
-
Hastie, T., R. Tibshirani, and J. Friedman, The Elements of Statistical Learning. Data Mining, Inference, and Prediction, Springer, New York, 2001.
-
(2001)
The Elements of Statistical Learning. Data Mining, Inference, and Prediction
-
-
Hastie, T.1
Tibshirani, R.2
Friedman, J.3
-
13
-
-
0242320493
-
Hyperparameter design criteria for support vector classifiers
-
Sept
-
Anguita, D., S. Ridella, F. Rivieccio, and R. Zunino, "Hyperparameter design criteria for support vector classifiers," Neurocomputing, Vol. 55, 109-134, Sept. 2003.
-
(2003)
Neurocomputing
, vol.55
, pp. 109-134
-
-
Anguita, D.1
Ridella, S.2
Rivieccio, F.3
Zunino, R.4
-
14
-
-
4944228528
-
-
Department of Computer Science and Information Engineering, National Taiwan University, July
-
Hsu, Ch.-W., Ch.-Ch. Chang, and Ch.-J. Lin, "A practical guide to support vector classification," Department of Computer Science and Information Engineering, National Taiwan University, July 2003.
-
(2003)
A practical guide to support vector classification
-
-
Hsu, C.-W.1
Chang, C.-C.2
Lin, C.-J.3
-
15
-
-
33749248713
-
A multi-source strategy based on a learning-by-examples technique for buried object detection
-
Bermani, E., A. Boni, S. Caorsi, M. Donelli, and A. Massa, "A multi-source strategy based on a learning-by-examples technique for buried object detection," PIER Journal, Vol. 48, 185-200, 2004.
-
(2004)
PIER Journal
, vol.48
, pp. 185-200
-
-
Bermani, E.1
Boni, A.2
Caorsi, S.3
Donelli, M.4
Massa, A.5
|