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Oil Spill Detection: A Case Study of Recurrent Artificial Neural Networks
University of Skövde, Department of Computer Science.ORCID iD: 0000-0001-6883-2450
University of Skövde, Department of Computer Science.
University of Skövde, Department of Computer Science.
1997 (English)Report (Other academic)
Abstract [en]

This paper summarizes and analyzes the results of a case study of artificial neural networks for the detection of oil spills from radar imagery, which has been carried as a joint project between the Connectionist Research Group, University of Skövde, and Ericsson Microwave Systems AB, Mölndal, Sweden.

Place, publisher, year, edition, pages
Skövde: University of Skövde , 1997.
Series
IDA Technical Reports ; HS-IDA-TR-97-001
Keywords [en]
artificial neural networks, oil spill detection, recurrent networks
National Category
Information Systems
Identifiers
URN: urn:nbn:se:his:diva-1234OAI: oai:DiVA.org:his-1234DiVA, id: diva2:2367
Note

HS-IDA-TR-97-001. Annotation: A. Browne (ed.) Neural Network Analysis, Architectures and Applications, IOP Press, Bristol, UK.

Available from: 2008-06-17 Created: 2008-06-17 Last updated: 2019-04-15Bibliographically approved

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Ziemke, TomBodén, MikaelNiklasson, Lars

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