Skip to main content

Remote sensing image analysis using a neural network and knowledge-based processing

Buy Article:

$55.00 plus tax (Refund Policy)

Abstract. In this paper, we propose a pattern classification method for remote sensing data using both a neural network and knowledge-based processing. A neural network has the ability to recognize complex patterns, and classifies them to one of the classes. However,the neural network might produce misclassification. A knowledge-based system which uses human geographical knowledge improves the classification results, compared with a conventional statistical method. The disadvantage of using a knowledge-based system is that it needs a large amount of knowledge to classify the data correctly. We propose a pattern classification method that integrates the advantages of both the neural network and knowledge-based system. The proposed system is divided into two subsystems which consist of recognition and error correction. We use the neural network for classification and the knowledge-based system for correcting misclassification created by the neural network. Experimental results are shown to illustrate the performance of the proposed system.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Document Type: Research Article

Publication date: 1997-03-10

More about this publication?
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more