An artificial neural network (ANN) based software package for classification of remotely sensed data

Computers and Geosciences

Volumn 22, Issue 1, 1996, Pages 81-87

  Mohanty, K K ^a   Majumdar, T J ^a  

^a INDIAN SPACE RESEARCH ORGANISATION   (India)

Author keywords

Artificial neural network; C; Classification; Remotely sensed data

Indexed keywords

ARTIFICIAL NEURAL NETWORK; CLASSIFICATION; COMPUTER PROGRAM; DATA PROCESSING; IRS- 1A; NEURAL NETWORK; REMOTE SENSING DATA; REMOTELY SENSED DATA;

EID: 0029730625     PISSN: 00983004     EISSN: None     Source Type: Journal    
DOI: 10.1016/0098-3004(95)00059-3     Document Type: Article

References (11)

1. Benediktsson, J. A., Swain, P. H., and Ersoy, O. K., 1990, Neural network approaches versus statistical methods on classification of multisource remote sensing data: IEEE Trans. on Geoscience and Remote Sensing, v. 28, no. 4, p. 540-552.
2. Bischof, H., Schneider, W., and Pinz, A. J., 1992, Multispectral classification of Landsat images using neural networks: IEEE Trans. on Geoscience and Remote Sensing, v. 30, no. 3, p. 482-490.
3. Brunak, S., and Lautrup, B., 1988, Neural networks - computers with intuition: World Scientific Publ. Co., River Edge, New Jersey, 180 p.
4. Fu, K. S., 1983, Pattern recognition techniques in remote sensing data analysis: Proc. Indian Acad. Sciences (Eng. Sciences), v. 6, no. 2, p. 153-175.
5. Heerman, P. D., and Khazenie, N., 1992, Classification of multi-spectral remote sensing data using a back-propagation neural network: IEEE Trans. on Geosciences and Remote Sensing, v. 30, no. 1, p. 81-88.
6. Jonathan, L., Ronald, C. W., Sengupta, S. K., and Welch, R. M., 1990, A neural network approach to cloud classification: IEEE Trans. on Geosciences and Remote Sensing, v. 28, no. 5, p. 846-855.
7. Lippman, R. P., 1987, An introduction to computing with neural nets: IEEE ASSP Magazine, v. 4, no. 2, p. 4-22.
8. Minsky, M. L., and Papert, S., 1969, Perceptrons: MIT Press, Cambridge, 258 p.
9. Mohanty, K. K., 1993, An artificial neural network approach for land cover classification: Proc. Nat. Symp. on Remote Sensing Applications for Resource Management with Special Emphasis on N. E. Region, Guwahati, p. 444-451.
10. Ritter, N. D., and Hepner, G. F., 1990, Application of an artificial neural network to land-cover classification of thematic mapper imagery: Computers & Geosciences, v. 16, no.6 p. 873-880.
11. Rumelhart, D. E., Hinton, G. E., and Williams, R. J., 1986, Learning representation by backpropagation errors: Nature, v. 323, no. 6088, p. 533-536.