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基于MobileNetV3Small-ECA的水稻病害轻量级识别研究

袁培森 欧阳柳江 翟肇裕 田永超

农业机械学报2024,Vol.55Issue(1):253-262,10.
农业机械学报2024,Vol.55Issue(1):253-262,10.DOI:10.6041/j.issn.1000-1298.2024.01.024

基于MobileNetV3Small-ECA的水稻病害轻量级识别研究

Lightweight Identification of Rice Diseases Based on Improved EC A and MobileNetV3 Small

袁培森 1欧阳柳江 1翟肇裕 1田永超2

作者信息

  • 1. 南京农业大学人工智能学院,南京 210095
  • 2. 南京农业大学人工智能学院,南京 210095||南京农业大学农学院,南京 210095
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摘要

Abstract

In order to realize the lightweight identification and detection of rice diseases,the ECA attention mechanism was used to improve the MobileNetV3Small model,and shared parameter transfer learning was used to carry out intelligent lightweight identification and detection of rice diseases.Pre-training was performed on the PlantVillage dataset,and the shared parameters obtained from the pre-training were transferred to the rice disease recognition model for fine-tuning and optimization.Experiments were on the open-source rice disease dataset.The experimental results showed that the recognition accuracy rate reached 97.47%under non-transfer learning,and 99.92%under transfer learning,while reducing the number of parameters by 26.69%.Secondly,the Grad-CAM was used for visualization.Compared with other attention mechanisms CBAM and SENET,the results generated by the ECA module were more consistent with the position and color of the disease spots in the image,indicating that the network can better focus on rice diseases.Characteristics,and the causes of misclassification were analyzed through visualization and each rice disease.The proposed method realized the lightweight of the rice disease recognition model,so that it can be deployed in resource-constrained scenarios such as mobile devices,and achieved the purpose of fast,efficient and portable.At the same time,an Android-based rice disease identification system was developed,which can facilitate the identification and analysis of rice diseases at the edge.

关键词

水稻病害识别/迁移学习/高效通道注意力机制/MobileNetV3Small/移动端部署

Key words

rice disease identification/transfer learning/ECA attention mechanism/MobileNetV3 Small/mobile deployment

分类

信息技术与安全科学

引用本文复制引用

袁培森,欧阳柳江,翟肇裕,田永超..基于MobileNetV3Small-ECA的水稻病害轻量级识别研究[J].农业机械学报,2024,55(1):253-262,10.

基金项目

国家自然科学基金项目(61502236)和江苏省农业科技自主创新资金项目(CX(21)3059) (61502236)

农业机械学报

OA北大核心CSTPCD

1000-1298

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