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Recurrent Artficial Neural Networks for the Detection of Oil Spills from Doppler Radar Imagery
University of Skövde, School of Humanities and Informatics.
1995 (English)Report (Other academic)
Abstract [en]

This paper discusses the application of artificial neural networks (ANNs) to the detection of oil spills in sea clutter environments from the classification of radar backscatter signals. A comparison and evaluation of different network architectures regarding reliability of dection and robustness to varying sea states/wind conditions shows that for this problem best results are achieved with a recurrent architecture similar to that of Elman's SRN.

Abstract [en]

Annotation: In Keating, John G. (ed.) Neural Computing - Research and Applications - Prodeedings of the Fifth Irish Neural Network Conference, St. Patrick's College, Maynooth, Co. Kildare, Ireland.

Place, publisher, year, edition, pages
Skövde: Institutionen för kommunikation och information , 1995.
Series
IKI Technical Reports, HS-IDA-TR-95-009
National Category
Information Science
Identifiers
URN: urn:nbn:se:his:diva-1239OAI: oai:DiVA.org:his-1239DiVA: diva2:2372
Available from: 2008-06-17 Created: 2008-06-17 Last updated: 2010-03-24

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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More styles
Language
  • de-DE
  • en-GB
  • en-US
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Output format
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