Cloud detection using probabilistic neural networks

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

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

7 Citations (Scopus)


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 languageEnglish
Title of host publicationInternational Geoscience and Remote Sensing Symposium (IGARSS)
Number of pages3
Publication statusPublished - 1 Dec 2001
Externally publishedYes
Event2001 International Geoscience and Remote Sensing Symposium (IGARSS 2001) - University of New South Wales, Sydney, NSW, Australia
Duration: 9 Jul 200113 Jul 2001


Conference2001 International Geoscience and Remote Sensing Symposium (IGARSS 2001)
CitySydney, NSW

ASJC Scopus subject areas

  • Computer Science Applications
  • Earth and Planetary Sciences(all)


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