Abstract The management of plant disease is a significant economic and environmental factor in the production of greenhouse tomato plants. Human expertise for assessing the presence and extent of disease is important in creating and implementing management plans, but it is difficult and expensive to acquire. In this paper, we present a new computer vision system to automatically recognize several diseases, detect previously unseen disease and to estimate per-leaf severity. Training and testing of models used several modified versions of the nine types of tomato disease of the PlantVillage tomato dataset and showed how different leaf properties impact disease detection.

中文翻译：

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一种番茄温室植物常见病害检测与严重程度评估系统

摘要 植物病害的管理是温室番茄植株生产中重要的经济和环境因素。评估疾病的存在和程度的人类专业知识对于制定和实施管理计划很重要，但获得它既困难又昂贵。在本文中，我们提出了一种新的计算机视觉系统来自动识别几种疾病，检测以前看不见的疾病并估计每片叶子的严重程度。模型的训练和测试使用了 PlantVillage 番茄数据集的九种番茄病害的几种修改版本，并展示了不同的叶子特性如何影响病害检测。