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Can I read Domain Translation of Images Using Auto Encoders and Coupled GANs with Unsupervised Learning on EtoBox?
Domain Translation of Images Using Auto Encoders and Coupled GANs with Unsupervised Learning by Vigneshkumar Arunachalam; Harikumar Rajaguru; Vinubama Krishnamoorthy; Viswanathan Varadaraj; Pavithra Ravikumar is a Engineering article available to read on EtoBox.
What is Domain Translation of Images Using Auto Encoders and Coupled GANs with Unsupervised Learning about?
## Abstract Domain translation of images is nothing but learning from marginal distribution across different to obtain a joint distribution from the listed domains. But there exist a limitless number of joint distributions, but we couldn’t infer that without additional assumptions. It is nothing but changing the entire scenario of the given input image by translating and reconstructing into an entirely new image but with the key features of the input image. Here for the domain translation of images from different domains in video, we are using Coupled-GAN’s for domain translation with making use of shared latent space.
Who reads Domain Translation of Images Using Auto Encoders and Coupled GANs with Unsupervised Learning?
It is typically read by researchers, students, and practitioners in Engineering.
- Author
- Vigneshkumar Arunachalam; Harikumar Rajaguru; Vinubama Krishnamoorthy; Viswanathan Varadaraj; Pavithra Ravikumar
- Publisher
- IOP Publishing
- Published
- 2021
- Language
- EN
- Field
- Engineering (Physical Sciences)