Frontiers in Plant Science (Jun 2023)

ASFL-YOLOX: an adaptive spatial feature fusion and lightweight detection method for insect pests of the Papilionidae family

  • Lijia Xu,
  • Xiaoshi Shi,
  • Xiaoshi Shi,
  • Zuoliang Tang,
  • Zuoliang Tang,
  • Yong He,
  • Ning Yang,
  • Wei Ma,
  • Chengyu Zheng,
  • Huabao Chen,
  • Taigang Zhou,
  • Peng Huang,
  • Zhijun Wu,
  • Yuchao Wang,
  • Zhiyong Zou,
  • Zhiliang Kang,
  • Jianwu Dai,
  • Yongpeng Zhao

DOI
https://doi.org/10.3389/fpls.2023.1176300
Journal volume & issue
Vol. 14

Abstract

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IntroductionInsect pests from the family Papilionidae (IPPs) are a seasonal threat to citrus orchards, causing damage to young leaves, affecting canopy formation and fruiting. Existing pest detection models used by orchard plant protection equipment lack a balance between inference speed and accuracy.MethodsTo address this issue, we propose an adaptive spatial feature fusion and lightweight detection model for IPPs, called ASFL-YOLOX. Our model includes several optimizations, such as the use of the Tanh-Softplus activation function, integration of the efficient channel attention mechanism, adoption of the adaptive spatial feature fusion module, and implementation of the soft Dlou non-maximum suppression algorithm. We also propose a structured pruning curation technique to eliminate unnecessary connections and network parameters.ResultsExperimental results demonstrate that ASFL-YOLOX outperforms previous models in terms of inference speed and accuracy. Our model shows an increase in inference speed by 29 FPS compared to YOLOv7-x, a higher mAP of approximately 10% than YOLOv7-tiny, and a faster inference frame rate on embedded platforms compared to SSD300 and Faster R-CNN. We compressed the model parameters of ASFL-YOLOX by 88.97%, reducing the number of floating point operations per second from 141.90G to 30.87G while achieving an mAP higher than 95%.DiscussionOur model can accurately and quickly detect fruit tree pest stress in unstructured orchards and is suitable for transplantation to embedded systems. This can provide technical support for pest identification and localization systems for orchard plant protection equipment.

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