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cs.CV2025
Manual Labelling Artificially Inflates Deep Learning-Based Segmentation Performance on RGB Images of Closed Canopy: Validation Using TLS
Matthew J. Allen, Harry J. F. Owen, Stuart W. D. Grieve +1
Monitoring forest dynamics at an individual tree scale is essential for accurately assessing ecosystem responses to climate change, yet traditional methods relying on field-based f…
cs.CV2025
PointsToWood: A deep learning framework for complete canopy leaf-wood segmentation of TLS data across diverse European forests
Harry J. F. Owen, Matthew J. A. Allen, Stuart W. D. Grieve +2
Point clouds from Terrestrial Laser Scanning (TLS) are an increasingly popular source of data for studying plant structure and function but typically require extensive manual proce…
cs.CV2024
Low-Cost Tree Crown Dieback Estimation Using Deep Learning-Based Segmentation
M. J. Allen, D. Moreno-Fernández, P. Ruiz-Benito +2
The global increase in observed forest dieback, characterised by the death of tree foliage, heralds widespread decline in forest ecosystems. This degradation causes significant cha…