ArticleInsects2023
A CNN-Based Method for Enhancing Boring Vibration with Time-Domain Convolution-Augmented Transformer.
Article in Insects, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Recognition of Wood-Boring Insect Creeping Signals Based on Residual Denoising Vision Network.Sensors (Basel, Switzerland) · 2025Article
- Automated Vibroacoustic Monitoring of Trees for Borer Infestation.Sensors (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Recording vibration signals induced by larvae activity in the trunk has proven to be an efficient method for detecting trunk-boring insects. However, the accuracy of the detection is often limited because the signals collected in real-world environments are heavily disrupted by environmental noises. To deal with this problem, we propose a deep-learning-based model that enhances trunk-boring vibration signals, incorporating an attention mechanism to optimize its performance. The training data utilized in this research consist of the boring vibrations of
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.