|本期目录/Table of Contents|

[1]张会敏,谢泽奇.基于知识图谱与深度学习的黄瓜叶部病害识别方法[J].江苏农业科学,2023,51(15):173-178.
 Zheng Huimin,et al.Cucumber leaf disease recognition based on knowledge graph and deep learning[J].Jiangsu Agricultural Sciences,2023,51(15):173-178.
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《江苏农业科学》[ISSN:1002-1302/CN:32-1214/S]

卷:
第51卷
期数:
2023年第15期
页码:
173-178
栏目:
农业工程与信息技术
出版日期:
2023-08-05

文章信息/Info

Title:
Cucumber leaf disease recognition based on knowledge graph and deep learning
作者:
张会敏谢泽奇
信阳农林学院信息工程学院,河南信阳 464000
Author(s):
Zheng Huiminet al
关键词:
知识图谱卷积神经网络作物病害识别数据融合黄瓜
Keywords:
-
分类号:
TP391.41
DOI:
-
文献标志码:
A
摘要:
黄瓜病害识别是病害防治的提前。针对现有作物病害识别方法中存在实体关系交叉关联、多源异构数据聚合能力差、依靠大规模标注数据、缺乏专家经验知识指导等问题,提出一种知识图谱与深度学习的黄瓜叶部病害识别方法(KGCNN)。该方法通过知识图谱与实体链接消歧嵌入获取作物病害知识图谱中的结构化病害知识,并将病害特征词向量与知识实体向量作为卷积神经网络的多通道输入,在卷积过程中从知识和语义2个层面表示不同病害类型。与现有的作物叶部病害识别方法相比,该方法充分利用了知识图谱和CNN分别在知识表示和特征学习方面的优势。在由黄瓜白粉病、斑点病和角斑病的病害叶片及其对应的环境气候气象信息的数据集上进行训练和测试。结果表明该方法的识别性能优于基于CNN及其改进模型和其他病害识别方法。该方法适用于作物初步病害识别,可为其他作物病害的识别提供技术支持。
Abstract:
-

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备注/Memo

备注/Memo:
收稿日期:2023-01-27
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,研究方向为计算机应用与图像处理。E-mail:513102773@qq.com。
通信作者:谢泽奇,硕士,副教授,研究方向为计算机应用。E-mail:xzq0413@163.com。
更新日期/Last Update: 2023-08-05