Let's assume I want to build a semantic segmentation algorithm, based on Multires-UNET. My GT-masks are messy and generated by a GAN, but they are getting better and better over time. The goal is knowledge expansion (based on the paper Noisy-Student).

Can you generally say that PreLU and Leaky Relu are better for noisy labels (or imperfect ones), like the situation in GANs in general?


Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Browse other questions tagged or ask your own question.