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An Adaptive State-Space Convolutional Fusion Network for High-Precision Pest Detection in Smart Agarwood Cultivation
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An Adaptive State-Space Convolutional Fusion Network for High-Precision Pest Detection in Smart Agarwood Cultivation
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An Adaptive State-Space Convolutional Fusion Network for High-Precision Pest Detection in Smart Agarwood Cultivation
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Journal Article
An Adaptive State-Space Convolutional Fusion Network for High-Precision Pest Detection in Smart Agarwood Cultivation
2025
Overview
The sustainable cultivation of agarwood, a high-value tree species, is significantly threatened by foliar pests, requiring efficient and accurate monitoring solutions. While deep learning is widely used, mainstream models face inherent limitations: Convolutional Neural Networks have restricted receptive fields and Transformers incur high computational complexity, complicating the balance of accuracy and efficiency for tiny pest detection in complex environments. To address these challenges, a novel Adaptive State-space Convolutional Fusion Network (ASCNet) is proposed. Its core component, the Adaptive State-space Convolutional Fusion Block (ASBlock), integrates the global context modeling of state-space models—which have linear complexity—with the local feature extraction of convolutional networks through a dual-path adaptive fusion mechanism. A Grouped Spatial Shuffle Downsampling (GSD) module replaces standard strided convolutions to preserve fine-grained spatial details during downsampling. For small object detection, a Normalized Wasserstein Distance (NWD)-based loss function mitigates the sensitivity of traditional IoU to minor localization errors. Evaluations on a new agarwood pest dataset show that ASCNet outperforms state-of-the-art detectors (including the YOLO series, RT-DETR, and Gold-YOLO), achieving a maximum mAP@50 of 93.0 ± 0.2% and mAP@50:95 of 71.2 ± 0.3% with high computational efficiency. The results confirm ASCNet as a robust and effective solution for intelligent pest monitoring in high-value crops like agarwood.
