Remote Sensing Image Analysis via a Texture Classification Neural Network

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6 Scopus citations

Abstract

In this work we apply a texture classification network to remote sensing image analysis. The goal is to extract the characteristics of the area depicted in the input image, thus achieving a segmented map of the region. We have recently proposed a combined neural network and rule-based framework for texture recognition. The framework uses unsupervised and supervised learning, and provides probability estimates for the output classes. We describe the texture classification network and extend it to demonstrate its application to the Landsat and Aerial image analysis domain.

Original languageEnglish
Title of host publicationAdvances in Neural Information Processing Systems 5, NIPS 1992
EditorsStephen Jose Hanson, Jack D. Cowan, C. Lee Giles
PublisherNeural information processing systems foundation
Pages425-432
Number of pages8
ISBN (Electronic)1558602747, 9781558602748
DOIs
StatePublished - 1992
Externally publishedYes
Event5th Advances in Neural Information Processing Systems, NIPS 1992 - Denver, United States
Duration: 30 Nov 19923 Dec 1992

Publication series

NameAdvances in Neural Information Processing Systems
Volume5
ISSN (Print)1049-5258

Conference

Conference5th Advances in Neural Information Processing Systems, NIPS 1992
Country/TerritoryUnited States
CityDenver
Period30/11/923/12/92

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