Improved SinGAN's Performance by Changing the Activation Function
Author:
Affiliation:
1. Graduate Program in Science and Technology Sophia University Tokyo 102‐8554 Japan
Publisher
Wiley
Subject
Electrical and Electronic Engineering
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/tee.23514
Reference7 articles.
1. ShahamTR DekelT MichaeliT.SinGAN: Learning a generative model from a single natural image.Proceedings of the IEEE International Conference on Computer Vision 2019; 4570–4580.
2. XuB WangN KongH ChenT LiM.Empirical evaluation of rectified activations in convolution network.arXiv:1505.00853 2015.https://arxiv.org/abs/1505.00853
3. RamachandranP ZophB LeQV.Searching for activation functions.ICLR; 1710.05941v2 2018.
4. Proposal of New Activation Function in Deep Image Prior
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