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Coral reef fish detection and recognition in underwater videos by supervised machine learning : Comparison between Deep Learning and HOG+SVM methods
Acte de colloque   Open Access

Coral reef fish detection and recognition in underwater videos by supervised machine learning : Comparison between Deep Learning and HOG+SVM methods

Sébastien Villon, Marc Chaumont, Gérard Subsol, Sébastien Villéger, Thomas Claverie et David Mouillot
ACIVS 2016 - 17th International Conference on Advanced Concepts for Intelligent Vision Systems (Lecce, Italy, 24/10/2016–27/10/2016)
2016

Résumé

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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