The Oil Radish Growth Dataset for Semantic Segmentation and Yield Estimation
Abstract
Data sharing in research is important in order to reproduce results, develop global models, and benchmark methods. This paper presents a dataset containing image and field data from a field plot experiment with oil radish (Raphanus sativus L. var oleiformis) as catch crop after spring barley. The field data consists of fresh weight, dry weight, Carbon content and Nitrogen content from multiple weekly plant samples collected from the plots. The image data consists of images collected weekly prior to the plant samples. A subset of the images corresponding to the plant sampling areas have been annotated pixelwise. In addition to the image and field data, weather data from the growing period is also included in the dataset. The dataset is accompanied by two challenges: 1) semantic segmentation of crops and 2) oil radish yield estimation. The former challenge focuses on data image, while the latter focuses on the field data. Baseline methods and results are provided for both challenges.
Cite
Text
Mortensen et al. "The Oil Radish Growth Dataset for Semantic Segmentation and Yield Estimation." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2019. doi:10.1109/CVPRW.2019.00328Markdown
[Mortensen et al. "The Oil Radish Growth Dataset for Semantic Segmentation and Yield Estimation." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2019.](https://mlanthology.org/cvprw/2019/mortensen2019cvprw-oil/) doi:10.1109/CVPRW.2019.00328BibTeX
@inproceedings{mortensen2019cvprw-oil,
title = {{The Oil Radish Growth Dataset for Semantic Segmentation and Yield Estimation}},
author = {Mortensen, Anders Krogh and Skovsen, Søren and Karstoft, Henrik and Gislum, René},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
year = {2019},
pages = {2703-2710},
doi = {10.1109/CVPRW.2019.00328},
url = {https://mlanthology.org/cvprw/2019/mortensen2019cvprw-oil/}
}