Mask, Train, Repeat! Artificial Intelligence for Quantitative Wood Anatomy

Mask, Train, Repeat! Artificial Intelligence for Quantitative Wood Anatomy

The recent developments in artificial intelligence have the potential to facilitate new research methods in ecology. Especially Deep Convolutional Neural Networks (DCNNs) have been shown to outperform other approaches in automatic image analyses. Here we apply a DCNN to facilitate quantitative wood...

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Bibliographic Details
Main Authors: Giulia Resente, Alexander Gillert, Mario Trouillier, Alba Anadon-Rosell, Richard L. Peters, Georg von Arx, Uwe von Lukas, Martin Wilmking
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-11-01
Series:Frontiers in Plant Science
Subjects:
artificial intelligence
wood anatomy
deep learning
lumen area
F1 score
ROXAS
Online Access:https://www.frontiersin.org/articles/10.3389/fpls.2021.767400/full

Internet

https://www.frontiersin.org/articles/10.3389/fpls.2021.767400/full

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