面向农作物病害识别的高阶残差卷积神经网络研究

doi:10.3969/j.issn.0253-2778.2019.10.002

中国科学技术大学学报 ›› 2019, Vol. 49 ›› Issue (10): 781-790.DOI: 10.3969/j.issn.0253-2778.2019.10.002

面向农作物病害识别的高阶残差卷积神经网络研究

曾伟辉，李淼，张健，黄小平，王敬贤，袁媛

1.中国科学院合肥智能机械研究所，安徽合肥 230031;2.中国科学技术大学信息学院，安徽合肥 230027

收稿日期:2018-06-30 修回日期:2018-09-28 接受日期:2018-09-28 出版日期:2019-10-31 发布日期:2018-09-28
通讯作者: 曾伟辉
作者简介:曾伟辉(通讯作者)，女，1982年生，博士生/副研究员.研究方向：农业信息化.E-mail: zengwhyu@163.com
基金资助:
十三五中科院信息化专项(XXH13505-03-104.)资助.

Research on high-order residual convolution neural network for crop disease recognition application

ZENG Weihui, LI Miao, ZHANG Jian, HUANG Xiaoping, WANG Jingxian, YUAN Yuan

1. Institute of Intelligent Machines, Chinese Academy of Sciences. Hefei 230031, China; 2. School of Information Science, University of Science and Technology of China. Hefei 230027, China

Received:2018-06-30 Revised:2018-09-28 Accepted:2018-09-28 Online:2019-10-31 Published:2018-09-28

摘要/Abstract

摘要： 当前研究农作物病害的准确识别工作中，针对简单背景的农作物病害图像识别取得了巨大成功，但当面向包含有各种噪声和复杂背景真实场景的农作物病害图像识别问题时，难以满足识别准确率的要求.为此提出了一种新的面向农作物病害识别应用的高阶残差卷积神经网络方法，以实现农作物病害的准确、抗干扰的识别.实验结果表明，该方法具有高准确率、强鲁棒性和良好的抗干扰能力，能较好地满足农作物病害识别的实际应用需求.

关键词: 农作物病害识别, 高阶残差, 鲁棒性, 卷积神经网络

Abstract: Current research works focusing on the image recognition of crop disease in simple background have achieved great success. However, when handling the problem of crop disease recognition with various noise and complex backgrounds, it is difficult to meet the requirement of recognition accuracy. To address these issues, a new high-order residual convolution neural network for crop disease recognition is proposed, which can realize crop disease recognition that is both accurate and anti-interference. Extensive experimental results demonstrate that the proposed method has high accuracy, strong robustness as well as good anti-interference ability, and can better meet the practical application requirements for crop disease recognition.

Key words: crop disease recognition, high-order residual(HOR), robustness, convolutional neural network (CNN)

中图分类号:

TP391

曾伟辉，李淼，张健，黄小平，王敬贤，袁媛. 面向农作物病害识别的高阶残差卷积神经网络研究[J]. 中国科学技术大学学报, 2019, 49(10): 781-790.

ZENG Weihui, LI Miao, ZHANG Jian, HUANG Xiaoping, WANG Jingxian, YUAN Yuan. Research on high-order residual convolution neural network for crop disease recognition application[J]. Journal of University of Science and Technology of China, 2019, 49(10): 781-790.

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面向农作物病害识别的高阶残差卷积神经网络研究

Research on high-order residual convolution neural network for crop disease recognition application

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