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Volumn 69, Issue 11, 2003, Pages 1225-1234

The Comparison of Activation Functions for Multispectral Landsat TM Image Classification

Author keywords

[No Author keywords available]

Indexed keywords

ACTIVATION ANALYSIS; ALGORITHMS; BACKPROPAGATION; NEUROLOGY;

EID: 0242415915     PISSN: 00991112     EISSN: None     Source Type: Journal    
DOI: 10.14358/PERS.69.11.1225     Document Type: Article
Times cited : (61)

References (33)
  • 5
    • 0005690050 scopus 로고
    • Classification of multispectral, multitemporal, multisource spatial data using artificial neural networks
    • 25-28 April, Reno, Nevada (American Society for Photogrammetry and Remote Sensing, Bethesda, Maryland)
    • Civco, D., and Y. Waug, 1994. Classification of multispectral, multitemporal, multisource spatial data using artificial neural networks, ASPRS/ACSM Annual Convention & Exposition, 25-28 April, Reno, Nevada (American Society for Photogrammetry and Remote Sensing, Bethesda, Maryland), pp. 123-133.
    • (1994) ASPRS/ACSM Annual Convention & Exposition , pp. 123-133
    • Civco, D.1    Waug, Y.2
  • 6
    • 0000875607 scopus 로고
    • Why two hidden layers are better than one
    • (Maureen Caudill, editor), 10-16 July, Washington, D.C. (Lawrence Erlbaum Associates, Inc.)
    • Chester, D.L., 1990. Why two hidden layers are better than one, Proceedings of the Winter 1990 International Joint Conference on Neural Networks (Maureen Caudill, editor), 10-16 July, Washington, D.C. (Lawrence Erlbaum Associates, Inc.), pp. 265-268.
    • (1990) Proceedings of the Winter 1990 International Joint Conference on Neural Networks , pp. 265-268
    • Chester, D.L.1
  • 7
    • 0024861871 scopus 로고
    • Approximation by superpositions of a sigmoidal function
    • Cybenko, G., 1989. Approximation by superpositions of a sigmoidal function, Mathematics Of Control, Signals and Systems, 2:303-314.
    • (1989) Mathematics of Control, Signals and Systems , vol.2 , pp. 303-314
    • Cybenko, G.1
  • 8
    • 0002983234 scopus 로고    scopus 로고
    • Remote sensing applications which may be addressed by neural networks using parallel processing technology
    • (I. Kanellopoulos, G.G. Wilkinson, F. Roli, and J. Austin, editors), Springer-Verlag, Berlin, Germany
    • Day, C., 1997. Remote sensing applications which may be addressed by neural networks using parallel processing technology, Neurocomputation in Remote Sensing Data Analysis (I. Kanellopoulos, G.G. Wilkinson, F. Roli, and J. Austin, editors), Springer-Verlag, Berlin, Germany, pp. 262-278.
    • (1997) Neurocomputation in Remote Sensing Data Analysis , pp. 262-278
    • Day, C.1
  • 9
    • 0000400323 scopus 로고    scopus 로고
    • Survey of neural transfer functions
    • Duch, W., and N. Jankovski, 1999. Survey of neural transfer functions, Neural Computing Surveys, 2:163-212.
    • (1999) Neural Computing Surveys , vol.2 , pp. 163-212
    • Duch, W.1    Jankovski, N.2
  • 10
    • 0029473455 scopus 로고
    • The effect of training set size and composition on artificial neural net classification
    • Foody, G.M., M.B. McCullagh, and W.B. Yates, 1995. The effect of training set size and composition on artificial neural net classification, International Journal of Remote Sensing, 16:1707-1723.
    • (1995) International Journal of Remote Sensing , vol.16 , pp. 1707-1723
    • Foody, G.M.1    McCullagh, M.B.2    Yates, W.B.3
  • 11
    • 0031105722 scopus 로고    scopus 로고
    • An evaluation of some factors affecting the accuracy of classification by an artificial neural network
    • Foody, G.M., and M.K. Arora, 1997. An evaluation of some factors affecting the accuracy of classification by an artificial neural network, International Journal of Remote Sensing, 18:799-810.
    • (1997) International Journal of Remote Sensing , vol.18 , pp. 799-810
    • Foody, G.M.1    Arora, M.K.2
  • 13
    • 0001793365 scopus 로고    scopus 로고
    • Improving neural network performance on the classification of complex geographic datasets
    • Gahegan, M., G. German, and G. West, 1999. Improving neural network performance on the classification of complex geographic datasets, Geographical Systems, 1:3-22.
    • (1999) Geographical Systems , vol.1 , pp. 3-22
    • Gahegan, M.1    German, G.2    West, G.3
  • 19
    • 0031105924 scopus 로고    scopus 로고
    • Textural neural network and version space classifiers for remote sensing
    • Kaminsky, E.J., H. Barad, and W. Brown, 1997. Textural neural network and version space classifiers for remote sensing, International Journal of Remote Sensing, 18(4):741-762.
    • (1997) International Journal of Remote Sensing , vol.18 , Issue.4 , pp. 741-762
    • Kaminsky, E.J.1    Barad, H.2    Brown, W.3
  • 20
    • 0031106314 scopus 로고    scopus 로고
    • Strategies and best practice for neural network image classification
    • Kanellopoulos, I., and G.G. Wilkinson, 1997. Strategies and best practice for neural network image classification, International Journal of Remote Sensing, 18(4):711-725.
    • (1997) International Journal of Remote Sensing , vol.18 , Issue.4 , pp. 711-725
    • Kanellopoulos, I.1    Wilkinson, G.G.2
  • 22
    • 0242599229 scopus 로고
    • Neural networks in finance & investing
    • (R.R. Trippi and E. Turban, editors.), Probus Publishing Company, Cambridge, United Kingdom
    • Klimasauskas, C., 1993. Neural networks in finance & investing, Applying Neural Networks (R.R. Trippi and E. Turban, editors.), Probus Publishing Company, Cambridge, United Kingdom, pp. 47-72.
    • (1993) Applying Neural Networks , pp. 47-72
    • Klimasauskas, C.1
  • 23
    • 0029472420 scopus 로고
    • A neural network as a nonlinear transfer function model for retrieving surface wind speeds from the special sensor microwave imager
    • Krasnopolsky, V.M., L.C. Breaker, and W.H. Gemmill, 1995. A neural network as a nonlinear transfer function model for retrieving surface wind speeds from the special sensor microwave imager, Journal of Geophysical Research, 100:11033-11045.
    • (1995) Journal of Geophysical Research , vol.100 , pp. 11033-11045
    • Krasnopolsky, V.M.1    Breaker, L.C.2    Gemmill, W.H.3
  • 24
    • 0023331258 scopus 로고
    • An introduction to computing with neural nets
    • April, 4-22
    • Lippmann, R.P., 1987. An introduction to computing with neural nets, IEEE ASSP Magazine, April, 4-22.
    • (1987) IEEE ASSP Magazine
    • Lippmann, R.P.1
  • 25
    • 0242514476 scopus 로고    scopus 로고
    • Choosing an optimal neural network size to aid search through a large image database
    • 13-16 September, University of Southampton, Southampton, United Kingdom
    • Messer, K., and J. Kittler, 1998. Choosing an optimal neural network size to aid search through a large image database, Proceedings of the Ninth British Machine Vision Conference (BMVC98), 13-16 September, University of Southampton, Southampton, United Kingdom, pp. 235-244.
    • (1998) Proceedings of the Ninth British Machine Vision Conference (BMVC98) , pp. 235-244
    • Messer, K.1    Kittler, J.2
  • 26
    • 0027205884 scopus 로고
    • A scaled conjugate gradient algorithm for fast supervised learning
    • Moller, M.F., 1993. A scaled conjugate gradient algorithm for fast supervised learning, Neural Networks, 6:525-533.
    • (1993) Neural Networks , vol.6 , pp. 525-533
    • Moller, M.F.1
  • 28
    • 0004548905 scopus 로고    scopus 로고
    • The use and effectiveness of artificial neural networks in forest fire classification
    • 08-10 September, Cardiff, United Kingdom
    • Özkan, C., and F. Sunar, 1999. The use and effectiveness of artificial neural networks in forest fire classification, RSS'99 Symposium on Earth Observation: From Data to Information, 08-10 September, Cardiff, United Kingdom, pp. 767-772.
    • (1999) RSS'99 Symposium on Earth Observation: from Data to Information , pp. 767-772
    • Özkan, C.1    Sunar, F.2
  • 30
    • 0031106246 scopus 로고    scopus 로고
    • Estimating surface radiation fluxes in the arctic from tovs brightness temperatures
    • Schweiger, A.J., and J.R. Key, 1997. Estimating surface radiation fluxes in the arctic from tovs brightness temperatures, International Journal of Remote Sensing, 18:955-970.
    • (1997) International Journal of Remote Sensing , vol.18 , pp. 955-970
    • Schweiger, A.J.1    Key, J.R.2
  • 31
    • 0035882616 scopus 로고    scopus 로고
    • Forest fire analysis with remote sensing data
    • Sunar, F., and C. Özkan, 2001. Forest fire analysis with remote sensing data, International Journal of Remote Sensing, 22(12):2265-2278.
    • (2001) International Journal of Remote Sensing , vol.22 , Issue.12 , pp. 2265-2278
    • Sunar, F.1    Özkan, C.2
  • 32
    • 0037945983 scopus 로고    scopus 로고
    • Open questions in neurocomputing for earth observation
    • (I. Kanellopoulos, G.G. Wilkinson, F. Roli, and J. Austin, editors), Springer-Verlag, Berlin, Germany
    • Wilkinson, G.G., 1997. Open questions in neurocomputing for earth observation, Neurocomputation in Remote Sensing Data Analysis (I. Kanellopoulos, G.G. Wilkinson, F. Roli, and J. Austin, editors), Springer-Verlag, Berlin, Germany, pp. 3-13.
    • (1997) Neurocomputation in Remote Sensing Data Analysis , pp. 3-13
    • Wilkinson, G.G.1
  • 33
    • 0033126073 scopus 로고    scopus 로고
    • Prediction and classification with neural network models
    • Zeng, L., 1999. Prediction and classification with neural network models, Sociological Methods and Research, 27(4):499-524.
    • (1999) Sociological Methods and Research , vol.27 , Issue.4 , pp. 499-524
    • Zeng, L.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.