In this work we present a flexible Open Source software platformfor training classifiers capable of identifying the taxonomy of a specimen fromdigital images. We demonstrate the performance of our system in a pilotstudy, building a feed-forward artificial neural network to effectively classifyfive different species of marine annelid worms of the class Polychaeta. Wealso discuss on the extensibility of the system, and its potential uses either asa research tool or in assisting routine taxon identification procedures.
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