Essays about: "WGAN"
Showing result 6 - 10 of 10 essays containing the word WGAN.
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6. Instability of a bi-directional TiFGAN in unsupervised speech representation learning
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : A major challenge in the application of machine learning in the speech domain is the unavailability of annotated data. Supervised machine learning techniques are highly dependent on the amount of labelled data and the quality of the labels. READ MORE
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7. Investigating the Learning Behavior of Generative Adversarial Networks
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Since their introduction in 2014, generative adversarial networks (GANs) have quickly become one of the most popular and successful frameworks for training deep generative models. GANs have shown exceptional results on different image generation tasks and they are known for their ability to produce realistic high- resolution images. READ MORE
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8. Synthesis of Tabular Financial Data using Generative Adversarial Networks
University essay from KTH/Matematisk statistikAbstract : Digitalization has led to tons of available customer data and possibilities for data-driven innovation. However, the data needs to be handled carefully to protect the privacy of the customers. Generative Adversarial Networks (GANs) are a promising recent development in generative modeling. READ MORE
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9. COMPARISON OF GENERATIVE ADVERSARIAL NETWORKS IN MEDICAL IMAGING APPLICATIONS - MR to CT image synthesis
University essay from Umeå universitet/Institutionen för datavetenskapAbstract : Cancer is one of the leading causes of death worldwide with about half of all cancer patients undergoing radiation therapy, either as a standalone treatmentor in combination with other methods such as chemotherapy. The dose planning of radiation therapy is based on medical images such as CT and MR images. READ MORE
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10. Future Frame Prediction with Generative Adversarial Networks
University essay from Lunds universitet/Matematik LTHAbstract : This report is about using generative adversarial networks with predictive coding networks for future frame prediction. Model selection choices for the components of the network are explored by training different models and testing their performance on next frame prediction in digital video from driving scenarios. READ MORE