mikeyEcology/MLWIC: MLWIC

  • Michael A. Tabak (Contributor)
  • Mohammad S. Norouzzadeh (Contributor)
  • David W. Wolfson (Contributor)
  • R. K. Boughton (Contributor)
  • Jake Ivan (Contributor)
  • Eric A. Odell (Contributor)
  • Eric Newkirk (Contributor)
  • Ryan K. Brook (Contributor)
  • Jesse Lewis (Contributor)
  • James C. Beasley (Contributor)
  • Kurt C. VerCauteren (Contributor)
  • Jeff Clune (Contributor)
  • Ryan S. Miller (Contributor)
  • Steven J. Sweeney (Contributor)
  • Nathan P. Snow (Contributor)
  • Joseph M. Halseth (Contributor)
  • Paul A. Di Salvo (Contributor)
  • Michael D. White (Contributor)
  • Ben Teton (Contributor)
  • Peter E. Schlichting (Contributor)
  • Bethany Wight (Contributor)
  • Paul M. Lukacs (Contributor)
  • Anna K. Moeller (Contributor)
  • Elizabeth G. Mandeville (Contributor)

Dataset

Description

Machine Learning for Wildlife Image Classification (MLWIC) is an R package that allows users to automatically classify animal species in camera trap images. The package comes with a build in model that was trained to recognize 27 species using over 3.7 million images. It works rapidly (> 2,000 images/minute on a laptop computer) and accurately (98% accuracy across all species). The package also allows users to train their own machine learning model to recognize species using images tht they have classified.
Date made availableOct 4 2018
PublisherZenodo

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