Abstract
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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CITATION STYLE
Villon, S., Chaumont, M., Subsol, G., Villéger, S., Claverie, T., & Mouillot, D. (2016). Coral reef fish detection and recognition in underwater videos by supervised machine learning: Comparison between deep learning and HOG+SVM methods. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10016 LNCS, pp. 160–171). Springer Verlag. https://doi.org/10.1007/978-3-319-48680-2_15
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