Open AccessDeep convolutional neural networks exploit high spatial and temporal resolution aerial imagery to predict key traits in miscanthus.
Author(s) -
Sebastián Varela,
Xuying Zheng,
Joyce Njuguna,
Erik J. Sacks,
Dylan Allen,
Jeremy Ruhter,
Andrew D. B. Leakey
Publication year - 2022
Publication title -
agrirxiv
Language(s) - English
Resource type - Journals
ISSN - 2791-1969
DOI - 10.31220/agrirxiv.2022.00155
Subject(s) - convolutional neural network , computer science , multispectral image , remote sensing , miscanthus , key (lock) , artificial intelligence , biomass (ecology) , environmental science , pattern recognition (psychology) , ecology , geography , bioenergy , biology , computer security , renewable energy