Cargando…

Automatic identification of species with neural networks

A new automatic identification system using photographic images has been designed to recognize fish, plant, and butterfly species from Europe and South America. The automatic classification system integrates multiple image processing tools to extract the geometry, morphology, and texture of the imag...

Descripción completa

Detalles Bibliográficos
Autores principales: Hernández-Serna, Andrés, Jiménez-Segura, Luz Fernanda
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4226643/
https://www.ncbi.nlm.nih.gov/pubmed/25392749
http://dx.doi.org/10.7717/peerj.563
_version_ 1782343652752752640
author Hernández-Serna, Andrés
Jiménez-Segura, Luz Fernanda
author_facet Hernández-Serna, Andrés
Jiménez-Segura, Luz Fernanda
author_sort Hernández-Serna, Andrés
collection PubMed
description A new automatic identification system using photographic images has been designed to recognize fish, plant, and butterfly species from Europe and South America. The automatic classification system integrates multiple image processing tools to extract the geometry, morphology, and texture of the images. Artificial neural networks (ANNs) were used as the pattern recognition method. We tested a data set that included 740 species and 11,198 individuals. Our results show that the system performed with high accuracy, reaching 91.65% of true positive fish identifications, 92.87% of plants and 93.25% of butterflies. Our results highlight how the neural networks are complementary to species identification.
format Online
Article
Text
id pubmed-4226643
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher PeerJ Inc.
record_format MEDLINE/PubMed
spelling pubmed-42266432014-11-12 Automatic identification of species with neural networks Hernández-Serna, Andrés Jiménez-Segura, Luz Fernanda PeerJ Biodiversity A new automatic identification system using photographic images has been designed to recognize fish, plant, and butterfly species from Europe and South America. The automatic classification system integrates multiple image processing tools to extract the geometry, morphology, and texture of the images. Artificial neural networks (ANNs) were used as the pattern recognition method. We tested a data set that included 740 species and 11,198 individuals. Our results show that the system performed with high accuracy, reaching 91.65% of true positive fish identifications, 92.87% of plants and 93.25% of butterflies. Our results highlight how the neural networks are complementary to species identification. PeerJ Inc. 2014-11-04 /pmc/articles/PMC4226643/ /pubmed/25392749 http://dx.doi.org/10.7717/peerj.563 Text en © 2014 Hernández-Serna and Jimenéz-Segura http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Biodiversity
Hernández-Serna, Andrés
Jiménez-Segura, Luz Fernanda
Automatic identification of species with neural networks
title Automatic identification of species with neural networks
title_full Automatic identification of species with neural networks
title_fullStr Automatic identification of species with neural networks
title_full_unstemmed Automatic identification of species with neural networks
title_short Automatic identification of species with neural networks
title_sort automatic identification of species with neural networks
topic Biodiversity
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4226643/
https://www.ncbi.nlm.nih.gov/pubmed/25392749
http://dx.doi.org/10.7717/peerj.563
work_keys_str_mv AT hernandezsernaandres automaticidentificationofspecieswithneuralnetworks
AT jimenezseguraluzfernanda automaticidentificationofspecieswithneuralnetworks