Closed wwjwy closed 3 years ago
Hi, Compared with fully-supervised learning, most of the semi/weakly-supervised learning just used different training strategies to learn from imperfect annotation. So I think your understanding is right. Best, Xiangde.
Sorry to interrupt you, I noticed that your weakly supervised and semi-supervised codes seem to differ only in the loss function. Therefore, I think that the semi-supervised model can be modified using a loss function to get a simple weakly supervised model. Can i understand this way? Thanks