11 基于深度残差网络的番茄细粒度病症识别

胡伟健;樊杰;杜永兴;李宝山;李灵芳;杨颜博;

• 1:内蒙古科技大学信息工程学院

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摘要(Abstract)：

将深度残差神经网络应用到农作物疾病识别中,对14类番茄细粒度病症进行识别,使用数据增强以及改变优化器等方式对深度残差网络进行优化.实验表明:调优后的深度残差网络在粗粒度番茄病症的识别中达到了97.18%的准确率,在细粒度番茄病症的识别中达到了81.68%的准确率,与传统的深度学习模型相比,有更好地识别效果.细粒度病症识别的研究,能够准确定位到疾病的严重程度,对番茄病症的治疗提供了准确的决策支持,有利于农业生产和环境保护.

关键词(KeyWords)： 深度学习;番茄病症;细粒度识别;深度残差网络

基金项目(Foundation): 国家自然科学基金资助项目(61661044;61961033);; 内蒙古自治区高等学校青年科技英才计划资助项目(NJYT-19-A15);; 内蒙古科技大学创新基金项目-优秀青年科学基金资助项目(2017YQL10)

作者(Author): 胡伟健;樊杰;杜永兴;李宝山;李灵芳;杨颜博;

Email:

DOI:

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