Book chapter
Deep learning for coral classification
Handbook of Neural Computation, pp.383-401
Academic Press
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
- Title
- Deep learning for coral classification
- Authors/Creators
- A. Mahmood (Author/Creator) - The University of Western AustraliaM. Bennamoun (Author/Creator) - The University of Western AustraliaS. An (Author/Creator) - The University of Western AustraliaF. Sohel (Author/Creator) - Murdoch UniversityF. Boussaid (Author/Creator) - School of EngineeringR. Hovey (Author/Creator) - The University of Western AustraliaG. Kendrick (Author/Creator) - The University of Western AustraliaR.B. Fisher (Author/Creator) - University of Edinburgh
- Contributors
- P. Samui (Editor)S.S. Roy (Editor)V. Balas (Editor)
- Publication Details
- Handbook of Neural Computation, pp.383-401
- Publisher
- Academic Press
- Identifiers
- 991005545165707891
- Copyright
- © 2017 Elsevier Inc.
- Murdoch Affiliation
- School of Engineering and Information Technology
- Language
- English
- Resource Type
- Book chapter
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