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Mamba-YOLO: A Hybrid Architecture with Linear-Complexity Selective Scan Mechanisms for Enhanced Microscopic Rice Disease Detection

2026-06-05

Abstract excerpt

<title>Abstract</title> <p>While automated visual inspection facilitates large-scale crop disease management, its deployment in field environments remains challenging. The morphological similarity of early-stage symptoms, combined with severe canopy occlusion, frequently degrades model accuracy. When applied to these unconstrained datasets, standard lightweight Convolutional Neural Networks (e.g., the YOLOv5-v11...

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Literature Corpus work: 51715f90-6de0-5cdd-b62d-8fa3aa298789
DOI: 10.21203/rs.3.rs-9928737/v1

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