|本期目录/Table of Contents|

[1]张会敏,谢泽奇,张善文.基于注意力胶囊网络的作物病害识别方法[J].江苏农业科学,2022,50(6):101-106.
 Zhang Huimin,et al.Study on crop disease recognition method based on attention capsule network[J].Jiangsu Agricultural Sciences,2022,50(6):101-106.
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基于注意力胶囊网络的作物病害识别方法(PDF)
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《江苏农业科学》[ISSN:1002-1302/CN:32-1214/S]

卷:
第50卷
期数:
2022年第6期
页码:
101-106
栏目:
植物保护
出版日期:
2022-03-20

文章信息/Info

Title:
Study on crop disease recognition method based on attention capsule network
作者:
张会敏12 谢泽奇12 张善文1
1.郑州西亚斯学院电子信息工程学院,河南郑州 451150; 2.信阳农林学院信息工程学院,河南信阳 464006
Author(s):
Zhang Huiminet al
关键词:
作物病害识别注意力机制胶囊网络注意力胶囊网络
Keywords:
-
分类号:
TP391.41
DOI:
-
文献标志码:
A
摘要:
因病害叶片图像的复杂多变性,较难准确分割病斑图像和提取到鲁棒的病害分类特征。现有的基于卷积神经网络(CNN)的作物病害识别方法通过扩展训练样本来增加大量不同角度、方向的训练样本,从而增强模型的鲁棒性和泛化能力,但需要较长的训练数据和较大的算力,并且对于一些少见的病斑不能准确识别,因此提出一种基于注意力胶囊网络(ACapsNet)的作物病害识别方法。ACapsNet中的注意力机制用于提高CapsNet的训练能力。ACapsNet中的胶囊由多个神经元组成,每个神经元表示图像中特定病斑的各种属性,这些属性能够表达不同类型病斑的形状、颜色、纹理、位置、大小和方向等特征,在复杂黄瓜病害叶片图像数据集上进行交叉验证试验。结果表明,ACapsNet能够有效表达不同病害叶片图像的各种特征,加快网络的训练速度,能够应用于田间复杂场景的作物病害识别系统。
Abstract:
-

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2021-06-05
基金项目:国家自然科学基金(编号:62072378);河南省教育厅高等学校重点科研项目(编号:20A520045)。
作者简介:张会敏(1981—),女,河南漯河人,硕士,副教授,研究方向为模式识别应用。E-mail:zhm0413@163.com。
通信作者:张善文,博士,教授,研究方向为模式识别及应用研究。E-mail:wjdw716@163.com。
更新日期/Last Update: 2022-03-20