Detecting emerald ash borer boring vibrations using an encoder‐decoder and improved <scp>DenseNet</scp> model

The development of VibroEABNet marks a significant advancement in pest detection methodologies, offering a scalable, accurate and efficient solution for early monitoring of wood-boring pests. The integration of a denoising module within the network structure addresses the challenge of environmental noise, one of the primary limitations in acoustic monitoring of pests. Currently, this research is limited to a specific pest. Future work will focus on the applicability of this network to other wood-boring pests. © 2024 Society of Chemical Industry.

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Publication Details

Journal
Pest Management Science
Published
2024-09-26
DOI
https://doi.org/10.1002/ps.8442
Citations
4
Primary Topic
Date Palm Research Studies
Type
article
Field-Weighted Citation Impact
2.40

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article

Detecting emerald ash borer boring vibrations using an encoder‐decoder and improved DenseNet model

Juhu Li, Haiyan Zhang, Zhibo Chen, Jinliang Yin
4 citations
Pest Management Science
Date Palm Research Studies
2.40
article

Detecting emerald ash borer boring vibrations using an encoder‐decoder and improved DenseNet model

Juhu Li, Haiyan Zhang, Zhibo Chen, Jinliang Yin
article en
4 citations

Abstract

The development of VibroEABNet marks a significant advancement in pest detection methodologies, offering a scalable, accurate and efficient solution for early monitoring of wood-boring pests. The integration of a denoising module within the network structure addresses the challenge of environmental noise, one of the primary limitations in acoustic monitoring of pests. Currently, this research is limited to a specific pest. Future work will focus on the applicability of this network to other wood-boring pests. © 2024 Society of Chemical Industry.

Pest Management ScienceVol. 81(1)
Beijing Forestry University (CN), State Forestry and Grassland Administration (CN)
National Natural Science Foundation of China
Responsible consumption and production
Openalex Percentile: Top 11%
Date Palm Research Studies
2.40
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