2023
DOI: 10.3390/insects14100819
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Feature Refinement Method Based on the Two-Stage Detection Framework for Similar Pest Detection in the Field

Hongbo Chen,
Rujing Wang,
Jianming Du
et al.

Abstract: Efficient pest identification and control is critical for ensuring food safety. Therefore, automatic detection of pests has high practical value for Integrated Pest Management (IPM). However, complex field environments and the similarity in appearance among pests can pose a significant challenge to the accurate identification of pests. In this paper, a feature refinement method designed for similar pest detection in the field based on the two-stage detection framework is proposed. Firstly, we designed a contex… Show more

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Cited by 2 publications
(1 citation statement)
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References 45 publications
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“…This modification reduced model parameters and computational workload while maintaining the original precision and improving detection speed on a maize pest dataset. Chen et al [25] introduced a refinement method for pest detection based on a two-stage detection framework. They proposed the context feature enhancement module, the region of interest (RoI) feature fusion module, and the non-task separation module to optimize the two-stage algorithm.…”
Section: Introductionmentioning
confidence: 99%
“…This modification reduced model parameters and computational workload while maintaining the original precision and improving detection speed on a maize pest dataset. Chen et al [25] introduced a refinement method for pest detection based on a two-stage detection framework. They proposed the context feature enhancement module, the region of interest (RoI) feature fusion module, and the non-task separation module to optimize the two-stage algorithm.…”
Section: Introductionmentioning
confidence: 99%