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The authors presents in this paper a novel fish classification methodology based on a combination between robust feature selection, image segmentation and geometrical parameter techniques using Artificial Neural Network and Decision Tree. Unlike existing works for fish classification, which propose descriptors and do not analyze their individual impacts in the whole classification task and do not make the combination between the feature selection, image segmentation and geometrical parameters, they propose a general set of features extraction using robust feature selection, image segmentation and geometrical parameters and their correspondent weights that should be used as a priori information by the classifier.
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