Unsupervised Domain Adaptation with Coupled Generative Adversarial Autoencoders
نویسندگان
چکیده
منابع مشابه
Adversarial Feature Augmentation for Unsupervised Domain Adaptation
Recent works showed that Generative Adversarial Networks (GANs) can be successfully applied in unsupervised domain adaptation, where, given a labeled source dataset and an unlabeled target dataset, the goal is to train powerful classifiers for the target samples. In particular, it was shown that a GAN objective function can be used to learn target features indistinguishable from the source ones...
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ژورنال
عنوان ژورنال: Applied Sciences
سال: 2018
ISSN: 2076-3417
DOI: 10.3390/app8122529