HyperLeaf2024 - A Hyperspectral Imaging Dataset for Classification and Regression of Wheat Leaves

William Michael Laprade, Pawel Tomasz Pieta, Svetlana Kutuzova, Jesper Cairo Westergaard, Mads Nielsen, Svend Christensen, Anders Bjorholm Dahl

CVPRW 2024 pp. 1234-1243

doi:10.1109/CVPRW63382.2024.00130 /cvprw/2024/laprade2024cvprw-hyperleaf2024/

Abstract

Hyperspectral imaging is a widely used method in remote sensing, particularly for use in airborne and satellite-based land surveillance. Its versatility is, however, much larger and has also seen usage in everything ranging from food processing and surveillance to astronomy and waste sorting. It is also gaining inroads with agricultural research. With most available datasets focusing on per-pixel classification, there is, however, a potential for hyperspectral whole-image analysis, but there is a severe lack of datasets for whole-image analysis. To help fill this gap and facilitate methodological development in whole-image hyperspectral image analysis, we introduce the Hy-perLeaf2024 dataset. The dataset consists of 2410 hyper-spectral images of wheat leaves, along with associated classification and regression targets at both the leaf level and the plot level. In addition to the dataset, we also provide experiments showing the importance of pretraining and highlighting the future research direction in whole-image hyper-spectral image analysis.

CVPRW Semantic Scholar

Cite

Text

Laprade et al. "HyperLeaf2024 - A Hyperspectral Imaging Dataset for Classification and Regression of Wheat Leaves." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2024. doi:10.1109/CVPRW63382.2024.00130

Markdown

[Laprade et al. "HyperLeaf2024 - A Hyperspectral Imaging Dataset for Classification and Regression of Wheat Leaves." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2024.](https://mlanthology.org/cvprw/2024/laprade2024cvprw-hyperleaf2024/) doi:10.1109/CVPRW63382.2024.00130

BibTeX

@inproceedings{laprade2024cvprw-hyperleaf2024,
  title     = {{HyperLeaf2024 - A Hyperspectral Imaging Dataset for Classification and Regression of Wheat Leaves}},
  author    = {Laprade, William Michael and Pieta, Pawel Tomasz and Kutuzova, Svetlana and Westergaard, Jesper Cairo and Nielsen, Mads and Christensen, Svend and Dahl, Anders Bjorholm},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2024},
  pages     = {1234-1243},
  doi       = {10.1109/CVPRW63382.2024.00130},
  url       = {https://mlanthology.org/cvprw/2024/laprade2024cvprw-hyperleaf2024/}
}