Cargando…
A CNN-Based Method for Enhancing Boring Vibration with Time-Domain Convolution-Augmented Transformer
SIMPLE SUMMARY: Trunk-boring insects have emerged as one of the most threatening forest pests globally, causing significant damage to forests. Certain groups of larvae reside within tree trunks without any observable external signs indicating their presence. This poses a significant challenge for pe...
Autores principales: | Zhang, Huarong, Li, Juhu, Cai, Gaoyuan, Chen, Zhibo, Zhang, Haiyan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10380367/ https://www.ncbi.nlm.nih.gov/pubmed/37504638 http://dx.doi.org/10.3390/insects14070631 |
Ejemplares similares
-
Multi-Channel Time-Domain Boring-Vibration-Enhancement Method Using RNN Networks
por: Xu, Xiaolin, et al.
Publicado: (2023) -
Acoustic Denoising Using Artificial Intelligence for Wood-Boring Pests Semanotus bifasciatus Larvae Early Monitoring
por: Liu, Xuanxin, et al.
Publicado: (2022) -
A Waveform Mapping-Based Approach for Enhancement of Trunk Borers’ Vibration Signals Using Deep Learning Model
por: Shi, Haopeng, et al.
Publicado: (2022) -
Modeling of Boring Mandrel Working Process with Vibration Damper
por: Sentyakov, Kirill, et al.
Publicado: (2020) -
Plant-CNN-ViT: Plant Classification with Ensemble of Convolutional Neural Networks and Vision Transformer
por: Lee, Chin Poo, et al.
Publicado: (2023)