I'm trying to build a Multi-Label Semantic Segmentation model, but while training, when I'm looking at the validation set, I can see that one label is far far behind, and in the end, he is not getting good results.
I'm using a U-net model with resnet50 backbone, tried categorial-cross-entropy loss, dice-loss, jaccord loss, but couldn't find a way to leverage this class.
I tried to give this class more weight in the loss function, I even tried to give this class over 90% and still thestates were low.
Someone have any Idea, method, a way of action, even tricks from his experience to help me with that issue? is it a common problem? or I need to check my basics?