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Image-based model parameter optimisation using Model-Assisted Generative Adversarial Networks
We propose and demonstrate the use of a model-assisted generative adversarial network (GAN) to produce fake images that accurately match true images through the variation of the parameters of the model that describes the features of the images. The generator learns the model parameter values that pr...
| Autores principales: | , |
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| Lenguaje: | eng |
| Publicado: |
2018
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| Acceso en línea: | https://dx.doi.org/10.1109/TNNLS.2020.2969327 http://cds.cern.ch/record/2652277 |