Training strategies for neural network soft classification of remotely-sensed imagery

International Journal of Remote Sensing

Volumn 18, Issue 8, 1997, Pages 1851-1856

  Bernard, A C ^a   Wilkinson, G G ^a,b   Kanellopoulos, I ^a  

^a JOINT RESEARCH CENTRE   (Italy)

^b KINGSTON UNIVERSITY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

IMAGE ANALYSIS; IMAGING TECHNIQUES; NEURAL NETWORKS; PATTERN RECOGNITION;

LAND COVER CLASSIFICATION; SOFT NEURAL NETWORK CLASSIFICATION;

REMOTE SENSING;

CLASSIFICATION; LAND COVER; NEURAL NETWORK; REMOTE SENSING; SOFT CLASSIFICATION; TRAINING;

EID: 0031142019     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/014311697218160     Document Type: Article

References (5)

1. Bixaghi, E., Brivio, P. A., and Rampini, A. (Editors), 1996. Soft Computing in Remote Sensing Data Analysis (Singapore: World Scientific).
2. Foody, G. M., and Cox, D. P., 1994, Sub-pixel land cover composition estimation using a linear mixture model and fuzzy membership functions. International Journal of Remote Sensing, 15, 619-631.
3. Richard, M. D., and Lippmann, R. P., 1991, Neural network classifiers estimate Bayesian a posteriori probabilities. Neural Computation. 3, 461-483.
4. Ruck, D. W., Rogers, S. K., Kabrisky, M., Oxley, M. E., and Suter, B. W., 1990, The multilayer perceptron as an approximation to a Bayes optimal discriminant function. IEEE Transactions on Neural Networks, 1, 296-298.
5. Wilkinson, G. G., Fierens, F., and Kanellopoulos, I., 1995, Integration of neural and statistical approaches in spatial data classification. Geographical Systems, 2, 1-20.