Mr. Keming Zhang Profile

Keming Zhang

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Proceedings Article | 10 October 2023 Paper

Area localization of leaf diseases under complex environments

Hanlin Wang, Keming Zhang, Yan Zou, Fenmei Fenme, Chenrui Kang, Hongbo Chen, Qingshan Xu

Proceedings Volume 12799, 1279923 (2023) https://doi.org/10.1117/12.3006213

KEYWORDS: Diseases and disorders, Object detection, Image segmentation, Agriculture, Feature extraction, Target detection, Computer vision technology, Spatial resolution, Reliability, Performance modeling

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Regional location of plant diseases helps to develop targeted prevention and control strategies to improve crop production efficiency and reduce agricultural losses. Recently, some important advances have been made in computer vision-based methods. However, most of the current mainstream methods are based on target detection or rotation detection, which always include environmental noise in the results of locating disease areas. In this paper, we revisit the task from the perspective of segmentation tasks and propose a feature reinforcement module. Specifically, we effectively focus on the shortcomings of previous methods where neighbourhood features cannot interact by looking at the shortcomings of the Feature Pyramid Network (FPN) in the feature extraction process through multi-scale features repetitive sampling. In addition, we compared the dataset annotation methods under different annotations such as target detection, rotation detection, and segmentation, and the visualisation well demonstrates the need to use segmentation methods. In the final experimental results, our method is proved to improve mAP by 1.3% and mIOU by 1% over state-of-the-art methods. A large number of methods have demonstrated the superiority and reliability of our method.

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