Database Reference
In-Depth Information
by the symmetric linked list (SLL) structure. Our future work is to enhance our
cascaded system by applying edge information. The edge information can be used
as an outline of the distribution of clusters because it can provide information
about the distribution of textures. We hope that by applying this information to our
system, the classification accuracy can be further improved.
8.6 References
[1] Kennedy, R. L., Lee, Y., Roy, B. V., Reed, C. D., and Lippmann, R. P., Solving
data mining problems through pattern recognition , Prentice Hall, 1998.
[2] Lippmann, R. P., Pattern classification using neural networks, IEEE Commu-
nications Magazine , pp. 47 - 54, 1989.
[3] Lu, H., Setiono, R., Liu, H., Effective data mining using neural networks,
IEEE Transactions on Knowledge and Data Engineering , 8, pp. 957 - 61, Dec.
1996.
[4] Introduction to the special issue on neural networks for data mining and
knowledge discovery, IEEE Transactions on Neural Networks , 11, May,
pp.545 - 9, 2000.
[5] Kaizer, H., A quantification of textures on aerial photographs, Boston Univ.
Res. Lab., Boston, Ma Tech. Note 121, AD 69484, 1955.
[6] Darling, E. M., and Joseph, R. D., Pattern recognition from satellite altitudes,
IEEE Trans. Syst. Sci. Cybern. , SSC-4, pp. 38 - 47, Mar. 1968.
[7] Haralick, R. M., Shanmugam, K., and Dinstein, I., Texture features for image
classification, IEEE Trans. Syst. Man Cybern. , 3, pp. 610 - 21, 1973.
[8] Boucher, J. M., Lena, P., and Marchand, J. F., Application of local and global
unsupervised Bayesian classification algorithms to the forest, IGARSS'93,
Better Understanding of Earth Environment (Cat. No. 93CH3294-6), 2, pp.
737 - 9, 1993.
[9] Rignot, E., and Chellappa, R., Segmentation of polarimetric synthetic aperture
radar data, IEEE Trans. Image Processing , 1 (3), pp. 281 - 99, Jul. 1997.
[10] Solberg, H. S., Taxt, T., and Jain, A. K., A Markov random field model for
classification of multisource satellite imagery, IEEE Trans. Geosci. Remote
Sensing , 34 (1), pp. 100 - 13, Jan. 1996.
[11] Hara, Y., Atkins, G., Yueh, S. H., Shin, R. T., and Kong, J. A., Application of
neural networks to radar image classification, IEEE Trans. Geosci. Remote
Sensing , 32 (1), pp. 100 - 9, Jan. 1994.
[12] Tzeng, Y. C., Chen, K. S., Kao, W. L., and Fung, A. K., A dynamic learning
neural network for remote sensing applications, IEEE Trans. Geosci. Remote
Sensing , 32 (5), pp. 994 - 1102, Sept. 1994.
[13] Tzeng, Y. C., and Chen, K. S., A fuzzy neural network to SAR image classifi-
cation, IEEE Trans. Geosci. Remote Sensing , 36 (1), pp. 301 - 7, Jan. 1998.
[14] Juang, C. F., and Lin, C. T., An on-line self-constructing neural fuzzy infer-
ence network for system modeling, IEEE Trans. Fuzzy Systems , 6 (1), Feb.
Search WWH ::




Custom Search