Högskolan i Skövde

his.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • apa-cv
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Oil Spill Detection from Doppler Radar Imagery using Artificial Neural Networks
University of Skövde, Department of Computer Science. (The Connectionist Research Group)ORCID iD: 0000-0001-6883-2450
Ground Systems Division, Ericsson Radar Electronics AB, Mölndal, Sweden.
1995 (English)Report (Other academic)
Abstract [en]

This paper reports on results of an ongoing project investigating the application of artificial neural networks (ANNs) to the classification/ cartography of sea clutter environments, and in particular the detection of oil spills, on the basis of their radar backscatter signals.

Place, publisher, year, edition, pages
Skövde: University of Skövde , 1995.
Series
IDA Technical Reports ; HS-IDA-TR-95-007
National Category
Information Systems
Identifiers
URN: urn:nbn:se:his:diva-1232OAI: oai:DiVA.org:his-1232DiVA, id: diva2:2365
Note

HS-IDA-TR-95-007

Annotation: In Bulsari & Kallio (eds.) Engineering Applications of Neural Networks - Proceedings of the International Conference EANN '95, Finnish Artificial Intelligence Society

Available from: 2008-06-17 Created: 2008-06-17 Last updated: 2021-05-21Bibliographically approved

Open Access in DiVA

No full text in DiVA

Authority records

Ziemke, Tom

Search in DiVA

By author/editor
Ziemke, Tom
By organisation
Department of Computer Science
Information Systems

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 268 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • apa-cv
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf