Deep Learning and Phenology Enhance Large-Scale Tree Species Classification in Aerial Imagery during a Biosecurity Response

Deep Learning and Phenology Enhance Large-Scale Tree Species Classification in Aerial Imagery during a Biosecurity Response

The ability of deep convolutional neural networks (deep learning) to learn complex visual characteristics offers a new method to classify tree species using lower-cost data such as regional aerial RGB imagery. In this study, we use 10 cm resolution imagery and 4600 trees to develop a deep learning m...

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Bibliographic Details
Main Authors: Grant D. Pearse, Michael S. Watt, Julia Soewarto, Alan Y. S. Tan
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Remote Sensing
Subjects:
tree species
classification
deep learning
convolutional networks
biosecurity
forest pathology
Online Access:https://www.mdpi.com/2072-4292/13/9/1789

Internet

https://www.mdpi.com/2072-4292/13/9/1789

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