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Automated species-level identification of planktic foraminifera using convolutional neural networks, with comparison to human performance

  • Published:2019-03 Issue: Volume:147 Page:16-24
  • ISSN:0377-8398
  • Container-title:Marine Micropaleontology
  • language:en
  • Short-container-title:Marine Micropaleontology

Author:

Mitra R.,Marchitto T.M.,Ge Q.,Zhong B.,Kanakiya B.,Cook M.S.,Fehrenbacher J.S.,Ortiz J.D.,Tripati A.,Lobaton E.

Funder

US National Science Foundation

US Department of Energy

Publisher

Elsevier BV

Subject

Paleontology,Oceanography

Reference36 articles.

1. TensorFlow: a system for large-scale machine learning;Abadi,2016

2. The application of expert systems to the identification and use of microfossils in the petroleum industry;Athersuch;Math. Geol.,1994

3. Palaeoceanographic implications of genetic variation in living North Atlantic Neogloboquadrina pachyderma;Bauch;Nature,2003

4. An ecological, zoogeographic and taxonomic review of recent planktonic Foraminifera;Bé,1977

5. Automatic recognition of coccoliths by dynamical neural networks;Beaufort;Mar. Micropaleontol.,2004

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