activity
20222025
most citedBenchmarking tree species classification from proximally-sensed laser scanning data: introducing the FOR-species20K dataset

5 citations · 6 across the 5 of their papers we have counts for

collaborators

6 papers

physics.soc-ph2025

AI4X Roadmap: Artificial Intelligence for the advancement of scientific pursuit and its future directions

Stephen G. Dale, Nikita Kazeev, Alastair J. A. Price +65

Artificial intelligence and machine learning are reshaping how we approach scientific discovery, not by replacing established methods but by extending what researchers can probe, p…

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★ 1 cited

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…

cs.CV2024★ 5 cited

Benchmarking tree species classification from proximally-sensed laser scanning data: introducing the FOR-species20K dataset

Stefano Puliti, Emily R. Lines, Jana Müllerová +30

Proximally-sensed laser scanning offers significant potential for automated forest data capture, but challenges remain in automatically identifying tree species without additional…

cs.AI2022

AI applications in forest monitoring need remote sensing benchmark datasets

Emily R. Lines, Matt Allen, Carlos Cabo +7

With the rise in high resolution remote sensing technologies there has been an explosion in the amount of data available for forest monitoring, and an accompanying growth in artifi…