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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?

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