Automated recognition by multiple convolutional neural networks of modern, fossil, intact and damaged pollen grains-Reference-Cited by-同舟云学术

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Automated recognition by multiple convolutional neural networks of modern, fossil, intact and damaged pollen grains

Published:2020-07 Issue: Volume:140 Page:104498
ISSN:0098-3004
Container-title:Computers & Geosciences
language:en
Short-container-title:Computers & Geosciences

Author:

Bourel Benjamin,Marchant Ross,de Garidel-Thoron Thibault,Tetard Martin,Barboni Doris,Gally Yves,Beaufort Luc

Funder

Aix-Marseille Université

FP7 People: Marie-Curie Actions

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Information Systems

Reference46 articles.

1. African Plant Database,2019

2. African Pollen Database,2019

3. TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems. arXiv:1603.04467.;Abadi,2016

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

5. Associations polliniques actuelles et quaternaires en Ethiopie (vallées de l'Awash et de l'Omo). PhD Dissertation;Bonnefille,1972

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