DocumentCode
1802841
Title
Comparison of two different PNN training approaches for satellite cloud data classification
Author
Tian, Bin ; Azimi-Sadjadi, Mahmood R. ; Gao, Wenfeng
Author_Institution
Dept. of Electr. & Comput. Eng., Colorado State Univ., Fort Collins, CO, USA
Volume
6
fYear
1999
fDate
36342
Firstpage
3791
Abstract
This paper presents a new training algorithm for probabilistic neural networks (PNNs) using the minimum classification error (MCE) criterion. A comparison is made between the MCE training scheme and the widely used maximum likelihood learning on a cloud classification problem using satellite imagery data
Keywords
clouds; geophysics computing; learning (artificial intelligence); neural nets; pattern classification; probability; remote sensing; Gaussian mixture model; cloud classification; maximum likelihood learning; minimum classification error; probabilistic neural networks; satellite cloud data; satellite imagery; Clouds; Computer errors; Electronic mail; Maximum likelihood estimation; Neural networks; Neurons; Parameter estimation; Pattern recognition; Satellites; Training data;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location
Washington, DC
ISSN
1098-7576
Print_ISBN
0-7803-5529-6
Type
conf
DOI
10.1109/IJCNN.1999.830757
Filename
830757
Link To Document