YOLOv12 is a new attention-based real-time object detector that reports higher accuracy than YOLOv10, YOLOv11, and RT-DETR variants at comparable or better speed and efficiency.
Designing network design strategies through gradient path analysis
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A two-stage UAV framework prunes redundant wildfire video clips via a policy network with station point mechanism and detects fire sources in real time using an improved YOLOv8 model.
citing papers explorer
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YOLOv12: Attention-Centric Real-Time Object Detectors
YOLOv12 is a new attention-based real-time object detector that reports higher accuracy than YOLOv10, YOLOv11, and RT-DETR variants at comparable or better speed and efficiency.
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Two-Stage Framework for Efficient UAV-Based Wildfire Video Analysis with Adaptive Compression and Fire Source Detection
A two-stage UAV framework prunes redundant wildfire video clips via a policy network with station point mechanism and detects fire sources in real time using an improved YOLOv8 model.