Coral reef fish detection and recognition in underwater videos by supervised machine learning : Comparison between Deep Learning and HOG+SVM methods
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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ACIVS_2016_VILLON_CHAUMONT_SUBSOL_VILLEGER_CLAVERIE_MOUILLOT_Coral_Reef_Fish_Detection_and_Recognition.pdf (5.34 Mo)
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