Segmentation and Classification of Coral for Oceanographic Surveys: A Semi-Supervised Machine Learning Approach (bibtex)
by M. Johnson-Roberson, S. Kumar, S. Williams
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.
Reference:
Segmentation and Classification of Coral for Oceanographic Surveys: A Semi-Supervised Machine Learning Approach (M. Johnson-Roberson, S. Kumar, S. Williams), In IEEE/OES Oceans - Asia Pacific, 2006.
Bibtex Entry:
@inproceedings{Johnson-Roberson2006a,
	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.},
	Author = {M. Johnson-Roberson and Kumar, S. and Williams, S.},
	Booktitle = {{IEEE/OES Oceans - Asia Pacific}},
	Date-Added = {2013-08-17 13:32:03 +0000},
	Date-Modified = {2013-08-17 13:32:34 +0000},
	Keywords = {conf},
	Owner = {mkj},
	Series = {Singapore},
	Timestamp = {2009.02.24},
	Title = {Segmentation and Classification of Coral for Oceanographic Surveys: A Semi-Supervised Machine Learning Approach},
	Year = {2006},
	Bdsk-Url-1 = {http://dx.doi.org/10.1109/OCEANSAP.2006.4393835}}
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