Please use this identifier to cite or link to this item: http://hdl.handle.net/10077/3782
Title: VeSTIS: A Versatile Semi- Automatic Taxon Identification System from Digital Images
Authors: Nikolaou, Nikos
Sampaziotis, Pantelis
Aplikioti, Marilena
Drakos, Andreas
Kirmitzoglou, Ioannis
Argyrou, Marina
Papamarkos, Nikos
Promponas, Vasilis J.
Keywords: digital image analysisopen sourcesemi-automatic taxon identification
Issue Date: 2010
Publisher: EUT Edizioni Università di Trieste
Source: Nikos Nikolaou [et al.], VeSTIS: A Versatile Semi- Automatic Taxon Identification System from Digital Images, in Pier Luigi Nimis and Régine Vignes Lebbe (eds.): “Tools for Identifying Biodiversity: Progress and Problems. Proceedings of the International Congress, Paris, September 20-22, 2010”, Trieste, EUT Edizioni Università di Trieste, 2010, pp. 231-236.
Abstract: 
In this work we present a flexible Open Source software platform
for training classifiers capable of identifying the taxonomy of a specimen from
digital images. We demonstrate the performance of our system in a pilot
study, building a feed-forward artificial neural network to effectively classify
five different species of marine annelid worms of the class Polychaeta. We
also discuss on the extensibility of the system, and its potential uses either as
a research tool or in assisting routine taxon identification procedures.
Type: Book Chapter
URI: http://hdl.handle.net/10077/3782
ISBN: 978-88-8303-295-0
Appears in Collections:Tools for Identifying Biodiversity: Progress and Problems

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