automatic identification of species with neural networks

Clicks: 208
ID: 177781
2014
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Abstract
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.
Reference Key
hernndez-serna2014peerjautomatic Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Andrés Hernández-Serna;Luz Fernanda Jiménez-Segura
Journal pediatrics
Year 2014
DOI
10.7717/peerj.563
URL
https://peerj.com/articles/563/
Keywords
Neural network fish plant feature extraction digital imagemedicine

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