It involves transferring knowledge learned from one task to another to improve the performance of the model. It is often used in domains where labeled data is scarce, such as in medical imaging.
It involves transferring knowledge learned from one task to another to improve the performance of the model. It is often used in domains where labeled data is scarce, such as in medical imaging.