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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:在研究中共享的数据共享是重要的,以便重现结果,开发全球模型和基准方法。本文介绍了包含来自油萝卜(Raphanus Sativus L. Var oleiformis)的场绘图实验的数据集,作为春季大麦的捕获作物。现场数据由从图案中收集的多个每周植物样品的新鲜重量,干重,碳含量和氮含量组成。图像数据包括在植物样本之前每周收集的图像。对应于工厂采样区域的图像的子集已经被释放的pix刀片。除了图像和字段数据之外,还包括来自越来越多的时间的天气数据也包括在数据集中。数据集伴随着两个挑战:1)作物的语义分割和2)油萝卜产量估计。前者挑战重点关注数据图像,而后者则重点介绍现场数据。为这两个挑战提供基线方法和结果。

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