Generation of Synthetic Data with Generative Adversarial Networks

Generation of Synthetic Data with Generative Adversarial Networks

The aim of synthetic data generation is to provide data that is not real for cases where the use of real data is somehow limited. For example, when there is a need for larger volumes of data, when the data is sensitive to use, or simply when it is hard to get access to the real data. Traditional met...

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Bibliographic Details
Main Author: Garcia Torres, Douglas
Format: Others
Language:English
Published: KTH, Skolan för elektroteknik och datavetenskap (EECS) 2018
Subjects:
Synthetic Data Generation
Generative Adversarial Networks
Machine Learning
Deep Learning
Neural Networks
Syntetisk Datagenerering
Generativa Adversariella Nätverk
Maskin-lärande
Djupt Lärande
Neurala Nätverk.
Computer and Information Sciences
Data- och informationsvetenskap
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254366

Internet

http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254366

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