ArticleFrontiers in plant science2026
PAD-Net: a lightweight end-to-end detector for pepper anthracnose in complex agricultural environments.
Article in Frontiers in plant science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Peppers are globally significant economic crops, but their yield is severely threatened by anthracnose. Automated detection remains challenging due to irregular lesion boundaries, drastic scale variations, complex backgrounds, and dense foliage occlusion. To address these issues, this study proposes PAD-Net, a lightweight end-to-end detector. Its LGMambaNet backbone synergizes DSwin-Mamba for deformable sliding window-based local modeling with FA-WTMamba for global frequency-domain analysis. A C3K2_PC module is introduced to capture multi-directional edge signals, enhancing sensitivity to blurred and multi-scale features. Furthermore, a DSSA module is designed to suppress background interference. Evaluated on the Pepper Anthracnose Dataset using standard COCO metrics, PAD-Net significantly outperforms the baseline DEIM model. Specifically, the PAD-Net nano version achieves an
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