A systematic study shows that tuning only the late layers of SAM's vision transformer gives the best memory-accuracy trade-off for biomedical segmentation.
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Parameter Efficient Fine-Tuning of Segment Anything Model for Biomedical Imaging
A systematic study shows that tuning only the late layers of SAM's vision transformer gives the best memory-accuracy trade-off for biomedical segmentation.