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Abstract Target detection in low-light environments has wide applications, but it faces challenges due to extremely weak photon responses, severe sensor noise, and broken target geometry. We propose a target detection architecture based on feature-level physical prior decoupling–Illumination-Guided and Reliability-aware YOLO (IGU-YOLO). First, we design a reliability-aware illumination gating module (UIG-Block) in the shallow backbone layers.
Abstract Accurate tomato instance segmentation in greenhouse scenes remains challenging because of fruit occlusion, instance contact, ambiguous boundaries, and the visual similarity between green fruits and leaves. This study presents a lightweight YOLO11n-seg framework that combines a morphology-based shape-boundary-driven (SBD) weighting strategy with the previously proposed CMPRD multi-scale context module.
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