SFFNet uses multi-scale dynamic dual-domain coupling and a synergistic feature pyramid network to reach 36.8 AP on VisDrone and 20.6 AP on UAVDT for UAV object detection.
DAMO-YOLO : A report on real-time object detection design
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A new PCB defect detection method using structure-guided masked pretraining and spatial continuity regularization achieves 85.5% mAP0.5 on the DsPCBSD+ dataset.
YOLOv11 delivers higher mean average precision on standard benchmarks than prior YOLO versions while keeping real-time inference speed through C3K2, SPPF, and C2PSA modules.
citing papers explorer
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SFFNet: Synergistic Feature Fusion Network With Dual-Domain Edge Enhancement for UAV Image Object Detection
SFFNet uses multi-scale dynamic dual-domain coupling and a synergistic feature pyramid network to reach 36.8 AP on VisDrone and 20.6 AP on UAVDT for UAV object detection.
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Structure-Guided Mixed Masked Pretraining and Spatial Continuity Regularization for Printed Circuit Board Defect Detection
A new PCB defect detection method using structure-guided masked pretraining and spatial continuity regularization achieves 85.5% mAP0.5 on the DsPCBSD+ dataset.
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YOLOv11 Demystified: A Practical Guide to High-Performance Object Detection
YOLOv11 delivers higher mean average precision on standard benchmarks than prior YOLO versions while keeping real-time inference speed through C3K2, SPPF, and C2PSA modules.