Weakly supervised localization model for plant disease based on Siamese networks

Jiyang Chen ¹, Jianwen Guo ¹, Hewei Zhang ¹

⁰Dongguan University of Technology, Dongguan, China.

Frontiers in Plant Science +

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October 14, 2024

View abstract on PubMed

Summary

This study introduces a Siamese neural network model for agricultural disease localization. The Agricultural Disease Precise Localization Class Activation Mapping (ADPL-CAM) algorithm accurately identifies diseased plant areas, improving detection accuracy and reducing false alarms.

Area Of Science

Agricultural Science
Computer Vision
Machine Learning

Background

Plant diseases pose a significant threat to crop yield and agricultural productivity.
Current image-based disease detection methods struggle with symptom variability, leading to high false alarm rates.

Purpose Of The Study

To develop an efficient, weakly supervised model for precise agricultural disease localization.
To improve the accuracy and reduce false alarms in plant disease detection systems.

Main Methods

Utilized a Siamese neural network with a weight-sharing mechanism to capture visual differences in diseased plants.
Developed and integrated the Agricultural Disease Precise Localization Class Activation Mapping (ADPL-CAM) algorithm for accurate localization.
Evaluated the model's performance on various network architectures, including ResNet50 and SPDNet.

Main Results

ADPL-CAM demonstrated superior performance across all tested network architectures compared to GradCAM and SmoothCAM.
Achieved a 3.96% higher top-1 accuracy and 27.09% higher average Intersection over Union (IoU) than GradCAM on ResNet50.
On the SPDNet architecture, ADPL-CAM reached 54.29% top-1 accuracy and 67.5% average IoU, outperforming other methods.

Conclusions

The developed Siamese network model with ADPL-CAM effectively localizes plant diseases.
The proposed method offers accurate and prompt identification and localization of diseased plant leaves.
This approach has the potential to significantly enhance disease management strategies in agriculture.

Keywords:

Siamese networks class activation mapping deep learning plant disease weakly supervised localization