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Deep learning for coral classification

Authors :
Mahmood, A.
Bennamoun, M.
An, S.
Sohel, F.
Boussaid, F.
Hovey, R.
Kendrick, G.
Fisher, R.B.
Mahmood, A.
Bennamoun, M.
An, S.
Sohel, F.
Boussaid, F.
Hovey, R.
Kendrick, G.
Fisher, R.B.
Source :
Mahmood, A., Bennamoun, M., An, S., Sohel, F. <
Publication Year :
2017

Abstract

This chapter presents a summary of the use of deep learning for underwater image analysis, in particular for coral species classification. Deep learning techniques have achieved the state-of-the-art results in various computer vision tasks such as image classification, object detection, and scene understanding. Marine ecosystems are complex scenes and hence difficult to tackle from a computer vision perspective. Automated technology to monitor the health of our oceans can facilitate in detecting and identifying marine species while freeing up experts from the repetitive task of manual annotation. Classification of coral species is a challenging task in itself and deep learning has a potential of solving this problem efficiently.

Details

Database :
OAIster
Journal :
Mahmood, A., Bennamoun, M., An, S., Sohel, F. <
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1013718211
Document Type :
Electronic Resource