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RiceMamba-DETR: efficient rice disease detection via hybrid Mamba-transformer architecture with cross-scale feature aggregation and large-scale dataset
Accurate rice disease detection in field imagery remains challenging because disease symptoms are often small, visually ambiguous, and embedded in cluttered scenes with overlapping leaves, variable illumination, and complex backgrounds. Existing CNN-based detectors offer fast inference but have limited capacity for lon...