Freezing the first four blocks or the whole backbone of YOLOv8/YOLOv10 can match or beat full fine-tuning while using less GPU memory, but aggressive freezing fails on heavily augmented single-class data.
YOLO V3 + VGG16-based automatic operations monitoring and analysis in a manufacturing workshop under Industry 4.0
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An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures
Freezing the first four blocks or the whole backbone of YOLOv8/YOLOv10 can match or beat full fine-tuning while using less GPU memory, but aggressive freezing fails on heavily augmented single-class data.