Biodiversity & Conservation

, Volume 6, Issue 2, pp 263–274

Image analysis, neural networks, and the taxonomic impediment to biodiversity studies

  • Paul J. D. Weeks
  • Kevin J. Gaston
Article

DOI: 10.1023/A:1018348204573

Cite this article as:
Weeks, P.J.D. & Gaston, K.J. Biodiversity and Conservation (1997) 6: 263. doi:10.1023/A:1018348204573

Abstract

The taxonomic impediment to biodiversity studies may be influenced radically by the application of new technology, in particular, desktop image analysers and neural networks. The former offer an opportunity to automate objective feature measurement processes, and the latter provide powerful pattern recognition and data analysis tools which are able to 'learn' patterns in multivariate data. The coupling of these technologies may provide a realistic opportunity for the automation of routine species identifications. The potential benefits and limitations of these technologies, along with the development of automated identification systems are reviewed.

biodiversity identification image analysis neural networks taxonomy. 

Copyright information

© Chapman and Hall 1997

Authors and Affiliations

  • Paul J. D. Weeks
    • 1
  • Kevin J. Gaston
    • 2
  1. 1.Department of EntomologyThe Natural History MuseumLondonUK
  2. 2.Department of Animal and Plant SciencesUniversity of SheffieldSheffieldUK

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