Learning from sonar data for the classification of underwater seabeds

Thesis

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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Authors: Atallah, L; Louis Atallah

• Publication date: 2005
• DOI: 10.5287/ora-rvz7axmdb
• Type of award: DPhil
• Level of award: Doctoral
• Awarding institution: University of Oxford
• Language: English
• Keywords: machine learning; underwater; sensors; classification; sonar; acoustics
• Subjects: Sensors; Ocean and coastal engineering