Applying YOLOv12 with physics-flavored augmentations yields high reported mAP on four underwater detection benchmarks, but the claims are weakened by missing code, variance, and inconsistent speed numbers.
An improved yolov5-based underwater object-detection framework,
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Improve Underwater Object Detection through YOLOv12 Architecture and Physics-informed Augmentation
Applying YOLOv12 with physics-flavored augmentations yields high reported mAP on four underwater detection benchmarks, but the claims are weakened by missing code, variance, and inconsistent speed numbers.