most citedImage Quality Assessment Techniques Show Improved Training and Evaluation of Autoencoder Generative Adversarial Networks

5 citations · 5 across the 1 of their papers we have counts for

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1 paper

cs.CV2017★ 5 cited

Image Quality Assessment Techniques Show Improved Training and Evaluation of Autoencoder Generative Adversarial Networks

Michael O. Vertolli, Jim Davies

We propose a training and evaluation approach for autoencoder Generative Adversarial Networks (GANs), specifically the Boundary Equilibrium Generative Adversarial Network (BEGAN),…