Segmentation and Classification of Coral for Oceanographic Surveys: A Semi-Supervised Machine Learning Approach
Conference Paper, Proceedings of IEEE/MTS Oceans: Asia Pacific (OCEANS '06), May, 2006
Abstract
This work presents a technique for the autonomous segmentation and classification of coral through the combination of visual and acoustic data. Autonomous Underwater Vehicles (AUVs) facilitate the live capture of multi-modal sensor information about coral reefs. Environmental monitoring of these reefs can be aided though the autonomous extraction and identification of certain coral species of interest. The technique presented employs a two phase procedure of segmentation and classification to gather statistics about coral density during autonomous missions with an AUV.
BibTeX
@conference{Johnson-Roberson-2006-130232,author = {M. Johnson-Roberson and S. Kumar and S. Williams},
title = {Segmentation and Classification of Coral for Oceanographic Surveys: A Semi-Supervised Machine Learning Approach},
booktitle = {Proceedings of IEEE/MTS Oceans: Asia Pacific (OCEANS '06)},
year = {2006},
month = {May},
}
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