Coral Reef Fish Detection and Recognition in Underwater Videos by Supervised Machine Learning: Comparison Between Deep Learning and HOG+SVM Methods
In this paper, we present two supervised machine learning methods to automatically detect and recognize coral reef fishes in underwater HD videos. The first method relies on a traditional two step approach: extraction of HOG features and use of a SVM classifier. The second method is based on Deep Learning. We compare the results of the two methods on real data and discuss their strengths and weaknesses.
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