Deep Image Representations for Coral Image Classification
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Healthy coral reefs play a vital role in maintaining biodiversity in tropical marine ecosystems. Remote imaging techniques have facilitated the scientific investigations of these intricate ecosystems, particularly at depths beyond 10 m where SCUBA diving techniques are not time or cost efficient. With millions of digital images of the seafloor collected using remotely operated vehicles and autonomous underwater vehicles (AUVs), manual annotation of these data by marine experts is a tedious, repetitive, and time-consuming task. It takes 10–30 min for a marine expert to meticulously annotate a single image. Automated technology to monitor the health of the oceans would allow for transformational ecological outcomes by standardizing methods to detect and identify species. This paper aims to automate the analysis of large available AUV imagery by developing advanced deep learning tools for rapid and large-scale automatic annotation of marine coral species. Such an automated technology would greatly benefit marine ecological studies in terms of cost, speed, and accuracy. To this end, we propose a deep learning based classification method for coral reefs and report the application of the proposed technique to the automatic annotation of unlabeled mosaics of the coral reef in the Abrolhos Islands, W.A., Australia. Our proposed method automatically quantified the coral coverage in this region and detected a decreasing trend in coral population, which is in line with conclusions drawn by marine ecologists.
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Mahmood, A.; Bennamoun, M.; An, Senjian; Sohel, F.; Boussaid, F.; Hovey, R.; Kendrick, G.; Fisher, R. (2016)© 2016 IEEE. Healthy coral reefs play a vital role in maintaining biodiversity in tropical marine ecosystems. Deep sea exploration and imaging have provided us with a great opportunity to look into the vast and complex ...
Mahmood, A.; Bennamoun, M.; An, Senjian; Sohel, F.; Boussaid, F.; Hovey, R.; Kendrick, G.; Fisher, R. (2017)© 2017 Elsevier Inc. All rights reserved. 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 ...
Quaternary corals from reefs in the Wakatobi Marine National Park, SE Sulawesi, Indonesia, show similar growth rates to modern corals from the same areaCrabbe, M; Wilson, Moyra; Smith, D (2006)We have used digital photography, image analysis and measurements in the field to determine the growth rates of Quaternary corals in the Wakatobi Marine National Park, Indonesia, and compared them to growth rates of similar ...