 Our proposed deep learning model uses an attention mechanism to enhance the detection of larval activity in tree trunks. This model was trained on a dataset consisting of vibration signals from larvae activity and environmental noise. The model was able to significantly improve the accuracy of the VGG-16 classifier, which is commonly used for detecting larval activity. This article was authored by Huang Zhong, Zhihuli, Daoyuan Kai, and others.