Datasets:
bands unknown | bands_shape listlengths 3 3 | bands_dtype stringclasses 1
value | band_metadata stringclasses 1
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End of preview. Expand in Data Studio
Tree Crown Segmentation
This dataset provides real multispectral imagery of Camellia oleifera tree crowns collected in a field environment in China. Captured using a UAV platform with a DJI Mavic 3 M drone featuring RGB and multispectral sensors, it offers high-resolution aerial data for semantic segmentation applications in agricultural monitoring. The dataset contains 595 images with pixel-level mask annotations.
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
The original train/test/val split has been preserved in the split column.
Citation
@article{peng2026uav,
title={UAV-based two-stage deep learning for tree crown segmentation and height estimation in Camellia oleifera plantations},
author={Peng, Yongkang and Yan, Enping and Xu, Xiaocheng and Mo, Dengkui and Wei, Wei},
journal={Ecological Informatics},
volume={96},
pages={103868},
year={2026},
publisher={Elsevier}
}
peng, . yongkang . (2026). experimental data [Figure]. Zenodo. https://doi.org/10.5281/zenodo.18505981
This dataset was reformatted from its original format to match HuggingFace standards.
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