DocumentCode
2134215
Title
Cloud detection using probabilistic neural networks
Author
Zhang, W.D. ; He, M.X. ; Mak, M.W.
Author_Institution
Ocean Remote Sensing Inst., Ocean Univ. of Qingdao, China
Volume
5
fYear
2001
fDate
2001
Firstpage
2373
Abstract
This paper investigates the application of a particular type of probabilistic neural networks, namely radial basis function (RBF) networks, to detecting cloud in NOAA/AVHRR images. Based on the images collected from the East China Sea, the paper compares the performance of RBF networks with that of traditional multi-layer perceptrons (MLPs). The main results show that RBF networks are able to handle complex atmospheric and oceanographic phenomena while MLPs could not. The internal representation of the RBF networks and MLPs are also detailed in this paper
Keywords
atmospheric techniques; clouds; geophysical signal processing; image recognition; radial basis function networks; East China Sea; MLPs; NOAA/AVHRR images; cloud detection; internal representation; multi-layer perceptrons; probabilistic neural networks; radial basis function networks; Character generation; Clouds; Gold; Neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium, 2001. IGARSS '01. IEEE 2001 International
Conference_Location
Sydney, NSW
Print_ISBN
0-7803-7031-7
Type
conf
DOI
10.1109/IGARSS.2001.978006
Filename
978006
Link To Document