A new fine-grained method for automated visual analysis of herbarium specimens: A case study for phenological data extraction.

Hervé GoëauAdán Mora-FallasJulien ChampNatalie L Rossington Love Susan J Mazer Erick Mata-MonteroAlexis JolyPierre Bonnet

Published in: Applications in plant sciences (2020)

This method has great potential for automating the analysis of reproductive structures in high-resolution images of herbarium sheets. Deeper investigations regarding the taxonomic scalability of this approach and its potential improvement will be conducted in future work.

Keyphrases

high resolution
deep learning
machine learning
air pollution
molecular dynamics
high throughput
electronic health record
current status
convolutional neural network
big data
human health
risk assessment
single cell
data analysis
fine needle aspiration