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.
Authors
- Juhu Li
- Haiyan Zhang (ORCID: https://orcid.org/0000-0002-8629-2838)
- Zhibo Chen (ORCID: https://orcid.org/0000-0002-2346-7530)
- Jinliang Yin
Institutions
- Beijing Forestry University (CN)
- State Forestry and Grassland Administration (CN)
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
Funders
- National Natural Science Foundation of China