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Thesis

Learning from sonar data for the classification of underwater seabeds

Abstract:

The increased use of sonar surveys for both industrial and leisure activities has motivated the research for cost effective, automated processed for seabed classification. Seabed classification is essential for many fields including dredging, environmental studies, fisheries research, pipeline and cable route surveys, marine archaeology and automated underwater vehicles. The advancement in both sonar technology and sonar data storage has led to large quantities of sonar data being collecte...

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Institution:
University of Oxford
Research group:
Sensors
Oxford college:
St Cross College
Role:
Author
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Division:
MPLS
Department:
Engineering Science
Role:
Author

Contributors

Division:
MPLS
Department:
Engineering Science
Role:
Supervisor
Publication date:
2005
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford
Language:
English
Keywords:
Subjects:
UUID:
uuid:11a17b77-6e17-409e-9a6e-d19c13b86709
Local pid:
ora:5363
Deposit date:
2011-05-23

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