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Deep learning for coral classification

Mahmood, A., Bennamoun, M., An, S., Sohel, F., Boussaid, F., Hovey, R., Kendrick, G. and Fisher, R.B. (2017) Deep learning for coral classification. In: Samui, P., Roy, S.S. and Balas, V., (eds.) Handbook of Neural Computation. Academic Press, pp. 383-401.

Link to Published Version: https://doi.org/10.1016/B978-0-12-811318-9.00021-1
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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.

Publication Type: Book Chapter
Murdoch Affiliation: School of Engineering and Information Technology
Publisher: Academic Press
Copyright: © 2017 Elsevier Inc.
URI: http://researchrepository.murdoch.edu.au/id/eprint/39097
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