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The Oil Radish Growth Dataset for Semantic Segmentation and Yield Estimation

机译:用于语义分割和产量估计的油萝卜生长数据集

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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.
机译:为了重现结果,开发全局模型和基准方法,研究中的数据共享非常重要。本文提出了一个数据集,其中包含来自田间试验的图像和田间数据,该试验以油bar(Raphanus sativus L. var oleiformis)为春季大麦后的作物。田间数据包括鲜重,干重,碳含量和氮含量,这些均来自地块每周采集的多个植物样品。图像数据包括在每周采集植物样本之前收集的图像。对应于植物采样区域的图像子集已按像素注释。除了图像和野外数据,来自生长期的天气数据也包括在数据集中。该数据集面临两个挑战:1)农作物的语义分割和2)油萝卜的产量估算。前者的挑战集中在数据图像上,而后者的挑战集中在现场数据上。提供了两种挑战的基线方法和结果。

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