现代信息科技2025，Vol.9Issue(11)：43-48,6.DOI:10.19850/j.cnki.2096-4706.2025.11.009
基于对比学习的番茄叶片病害识别研究
Research on Tomato Leaf Disease Recognition Based on Contrastive Learning
黄忠平1
作者信息
- 1. 安徽理工大学 计算机科学与工程学院,安徽 淮南 232001
- 折叠
摘要
Abstract
In view of the current situation that traditional Deep Learning models exhibit low recognition accuracy and limited generalization ability in the process of tomato leaf disease recognition,this paper proposes a recognition model based on the Supervised Contrastive Learning method.The model proposes the AMECA module based on Channel Attention,which effectively captures the dependencies among channels,enhances the model's channel fusion ability,and improves the recognition performance.The AMECA module is integrated into ResNet18 model as an image feature extractor,and a high-precision tomato leaf disease recognition model is trained through the Supervised Contrastive Learning method.The experimental results on the tomato leaf disease dataset show that the accuracy of the model reaches 99.198%,which is 3.208%higher than that of the original ResNet18 model.Compared with some other traditional Convolutional Neural Networks,it has higher recognition accuracy and can better recognize tomato leaf diseases.It is applicable to tomato leaf images obtained in natural scenes,and demonstrates strong practicability.关键词
注意力机制/番茄叶片病害识别/图像识别/对比学习Key words
Attention Mechanism/tomato leaf disease recognition/image recognition/Contrastive Learning分类
信息技术与安全科学引用本文复制引用
黄忠平..基于对比学习的番茄叶片病害识别研究[J].现代信息科技,2025,9(11):43-48,6.
