Individual-tree identification of Korean pine based on UAV imagery and Mask R-CNN.
- DOI
- 10.13287/j.1001-9332.202605.007
- Published
- 2026 May
- Container
- Ying yong sheng tai xue bao = The journal of applied ecology
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.13287/j.1001-9332.202605.007,
title = {Individual-tree identification of Korean pine based on UAV imagery and Mask R-CNN.},
author = {Chen H and Quan Y and Ma XT and Bian SJ and Wang B and Li MZ},
year = {2026},
journal = {Ying yong sheng tai xue bao = The journal of applied ecology},
doi = {10.13287/j.1001-9332.202605.007},
url = {https://doi.org/10.13287/j.1001-9332.202605.007}
}RIS
TY - JOUR TI - Individual-tree identification of Korean pine based on UAV imagery and Mask R-CNN. AU - Chen H AU - Quan Y AU - Ma XT AU - Bian SJ AU - Wang B AU - Li MZ PY - 2026 JO - Ying yong sheng tai xue bao = The journal of applied ecology DO - 10.13287/j.1001-9332.202605.007 UR - https://doi.org/10.13287/j.1001-9332.202605.007 ER -
APA
H, C., Y, Q., XT, M., SJ, B., B, W., & MZ, L. (2026). Individual-tree identification of Korean pine based on UAV imagery and Mask R-CNN.. Ying yong sheng tai xue bao = The journal of applied ecology. https://doi.org/10.13287/j.1001-9332.202605.007
Source records
- pubmed · retrieved 2026-09-26T12:35:51.646Z