Identifying Multiple Apple Leaf Diseases Based on the Improved CBAM-ResNet18 Model Under Weak Supervision

Identifying Multiple Apple Leaf Diseases Based on the Improved CBAM-ResNet18 Model Under Weak Supervision

To deal with the issues of low accuracy of apple leaf disease images recognition under weak supervision with only image category labeling, an improved CBAM-ResNet-based algorithm was proposed in this research. Using ResNet18 as the base model, the multilayer perceptron (MLP) in the lightweight convo...

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Bibliographic Details
Main Authors: ZHANG Wenjing, JIANG Zezhong, QIN Lifeng
Format: Article
Language:English
Published: Editorial Office of Smart Agriculture 2023-03-01
Series:智慧农业
Subjects:
disease identification
residual network
attentional mechanisms
cosine annealing learning rate
transfer learning
convolutional block attention module (cbam)
multilayer perceptron (mlp)
Online Access:http://www.smartag.net.cn/CN/10.12133/j.smartag.SA202301005

Internet

http://www.smartag.net.cn/CN/10.12133/j.smartag.SA202301005

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