Referenced Items are not available for this document.
A novel temporal updating approach for probabilistic neural network classifiers was developed by Tian et al. (2000) to account for temporal changes of spectral and temperature features of clouds in the visible and infrared GOES 8 (Geostationary Operational Environmental Satellite) imagery data. In this paper, a new method referred to as moving singular value decomposition (MSVD) is introduced to improve the classification rate of the boundary blocks or blocks containing cloud types with non-uniform texture. The MSVD method is then incorporated into the temporal updating scheme and its effectiveness is demonstrated on several sequences of GOES 8 cloud imagery data. These results indicate that the incorporation of the new MSVD improves the overall performance of the temporal updating process by almost 10%
Published in:
Neural Networks, IEEE Transactions on
(Volume:12
,
Issue:
5
)
Date of Publication: Sep 2001
- Page(s):
- 1196 - 1203
- ISSN :
- 1045-9227
- INSPEC Accession Number:
- 7067109
- Digital Object Identifier :
- 10.1109/72.950147
- Product Type:
- Journals & Magazines
- Date of Current Version :
- 07 August 2002
- Issue Date :
- Sep 2001
- Sponsored by :
- IEEE Computational Intelligence Society
About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies
A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2013 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.
