plant_diseases:使用神经网络对植物病害进行分类

上传者: 42110533 | 上传时间: 2022-09-12 14:51:12 | 文件大小: 10.45MB | 文件类型: ZIP
植物病害分类 使用图像数据和神经网络对植物病害进行分类 该存储库包含用于训练几个深度卷积神经网络(CNN)的代码和相关分析,以识别14种作物物种和26种疾病。 使用在受控条件下收集并由PlantVillage项目提供的54306张患病和健康植物叶片图像的公共数据集对模型进行了训练。 评估了三种不同的方法来提高Mohanty等人报告的基线准确性。 在研究论文“将深度学习用于基于图像的植物病害检测”中,其中CNN模型也用于使用相同的数据集对植物病害进行分类。 研究的三种方法是“转移学习”,“单图像超分辨率”和“层次结构超类学习”,所有这些方法都集中于此数据集或图像分类问题所特有的特定组件。 项目组织 ├── LICENSE ├── Makefile <- Makefile with commands like `make data` or `make train` ├─

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