Cloud detection using probabilistic neural networks

W. D. Zhang; M. X. He; Man Wai Mak

Cloud detection using probabilistic neural networks

W. D. Zhang
, M. X. He
, Man Wai Mak

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

9 Citations (Scopus)

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 oceano-graphic phenomena while MLPs could not. The internal representation of the RBF networks and MLPs are also detailed in this paper.

Original language	English
Title of host publication	International Geoscience and Remote Sensing Symposium (IGARSS)
Pages	2373-2375
Number of pages	3
Publication status	Published - 1 Dec 2001
Externally published	Yes
Event	2001 International Geoscience and Remote Sensing Symposium (IGARSS 2001) - University of New South Wales, Sydney, NSW, Australia Duration: 9 Jul 2001 → 13 Jul 2001

Conference

Conference	2001 International Geoscience and Remote Sensing Symposium (IGARSS 2001)
Country/Territory	Australia
City	Sydney, NSW
Period	9/07/01 → 13/07/01

ASJC Scopus subject areas

Computer Science Applications
General Earth and Planetary Sciences

Cite this

@inproceedings{a8c30866a76b4c9fa4ddbf61a897de3e,

title = "Cloud detection using probabilistic neural networks",

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 oceano-graphic phenomena while MLPs could not. The internal representation of the RBF networks and MLPs are also detailed in this paper.",

author = "Zhang, \{W. D.\} and He, \{M. X.\} and Mak, \{Man Wai\}",

year = "2001",

month = dec,

day = "1",

language = "English",

pages = "2373--2375",

booktitle = "International Geoscience and Remote Sensing Symposium (IGARSS)",

note = "2001 International Geoscience and Remote Sensing Symposium (IGARSS 2001) ; Conference date: 09-07-2001 Through 13-07-2001",

}

TY - GEN

T1 - Cloud detection using probabilistic neural networks

AU - Zhang, W. D.

AU - He, M. X.

AU - Mak, Man Wai

PY - 2001/12/1

Y1 - 2001/12/1

N2 - 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 oceano-graphic phenomena while MLPs could not. The internal representation of the RBF networks and MLPs are also detailed in this paper.

AB - 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 oceano-graphic phenomena while MLPs could not. The internal representation of the RBF networks and MLPs are also detailed in this paper.

UR - https://www.scopus.com/pages/publications/0035572042

M3 - Conference article published in proceeding or book

SP - 2373

EP - 2375

BT - International Geoscience and Remote Sensing Symposium (IGARSS)

T2 - 2001 International Geoscience and Remote Sensing Symposium (IGARSS 2001)

Y2 - 9 July 2001 through 13 July 2001

ER -

Cloud detection using probabilistic neural networks

Abstract

Conference

ASJC Scopus subject areas

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Cite this