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.
Bi2f-yolo: A novel framework for underwater object detection based on yolov7,
1 Pith paper cite this work, alongside 11 external citations. Polarity classification is still indexing.
1
Pith paper citing it
11
external citations · OpenAlex
fields
cs.CV 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
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.