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...

Full description

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

Similar Items

Multivariate Time Series Data Generation using Generative Adversarial Networks : Generating Realistic Sensor Time Series Data of Vehicles with an Abnormal Behaviour using TimeGAN
by: Nord, Sofia
Published: (2021)

Deep Learning for Sea-Ice Classification on Synthetic Aperture Radar (SAR) Images in Earth Observation : Classification Using Semi-Supervised Generative Adversarial Networks on Partially Labeled Data
by: Staccone, Francesco
Published: (2020)

Privacy-Preserving Synthetic Medical Data Generation with Deep Learning
by: Torfi, Amirsina
Published: (2020)

Automatic Question Paraphrasing in Swedish with Deep Generative Models
by: Lindqvist, Niklas
Published: (2021)

Synthetic Data Generation for the Financial Industry Using Generative Adversarial Networks
by: Ljung, Mikael
Published: (2021)

HEMIGEN: Human Embryo Image Generator Based on Generative Adversarial Networks
by: Darius Dirvanauskas, et al.
Published: (2019-08-01)

Synthetic Electronic Medical Record Generation using Generative Adversarial Networks
by: Beyki, Mohammad Reza
Published: (2021)

Generating Synthetic Sidescan Sonar Snippets Using Transfer-Learning in Generative Adversarial Networks
by: Yannik Steiniger, et al.
Published: (2021-02-01)

Synthetic demand data generation for individual electricity consumers: Generative Adversarial Networks (GANs)
by: Korn, R., et al.
Published: (2022)

FGGAN: Feature-Guiding Generative Adversarial Networks for Text Generation
by: Yang Yang, et al.
Published: (2020-01-01)

Complementary Photoplethysmogram Synthesis From Electrocardiogram Using Generative Adversarial Network
by: Heean Shin, et al.
Published: (2021-01-01)

Generating adversarial examples without specifying a target model
by: Gaoming Yang, et al.
Published: (2021-09-01)

Generative Adversarial Network Synthesis of Hyperspectral Vegetation Data
by: Andrew Hennessy, et al.
Published: (2021-06-01)

Generation of Synthetic Images with Generative Adversarial Networks
by: Zeid Baker, Mousa
Published: (2018)

Generating Realistic Users Using Generative Adversarial Network With Recommendation-Based Embedding
by: Parichat Chonwiharnphan, et al.
Published: (2020-01-01)

SynSigGAN: Generative Adversarial Networks for Synthetic Biomedical Signal Generation
by: Debapriya Hazra, et al.
Published: (2020-12-01)

Deep Generative Adversarial Networks for Image-to-Image Translation: A Review
by: Aziz Alotaibi
Published: (2020-10-01)

Generating Synthetic Schematics with Generative Adversarial Networks
by: Daley Jr, John
Published: (2020)

Scenario Generation for Wind Power Using Improved Generative Adversarial Networks
by: Congmei Jiang, et al.
Published: (2018-01-01)

Synthetic Dataset of Electroluminescence Images of Photovoltaic Cells by Deep Convolutional Generative Adversarial Networks
by: Aragonés, J.I.M, et al.
Published: (2023)

Unsupervised Anomaly Detection on Multi-Process Event Time Series
by: Vendramin, Nicoló
Published: (2018)

SAR-to-Optical Image Translation Based on Conditional Generative Adversarial Networks—Optimization, Opportunities and Limits
by: Mario Fuentes Reyes, et al.
Published: (2019-09-01)

Coverless Image Steganography Based on Generative Adversarial Network
by: Jiaohua Qin, et al.
Published: (2020-08-01)

Effects of Transfer Learning on Data Augmentation with Generative Adversarial Networks
by: Berglöf, Olle, et al.
Published: (2019)

Generative adversarial networks for single image super resolution in microscopy images
by: Gawande, Saurabh
Published: (2018)

IMPROVING THE REALISM OF SYNTHETIC IMAGES THROUGH THE MIXTURE OF ADVERSARIAL AND PERCEPTUAL LOSSES
by: Atapattu, Charith Nisanka
Published: (2018)

Generating a synthetic dataset for kidney transplantation using generative adversarial networks and categorical logit encoding
by: Bartocci, John Timothy
Published: (2021)

Recent Progress on Generative Adversarial Networks (GANs): A Survey
by: Zhaoqing Pan, et al.
Published: (2019-01-01)

Text Analysis in Fashion : Keyphrase Extraction
by: Lin, Yuhao
Published: (2020)

Icon Generation Based on Generative Adversarial Networks
by: Hongyi Yang, et al.
Published: (2021-08-01)

DeepMoney: counterfeit money detection using generative adversarial networks
by: Toqeer Ali, et al.
Published: (2019-09-01)

Aerial Image Road Extraction Based on an Improved Generative Adversarial Network
by: Xiangrong Zhang, et al.
Published: (2019-04-01)

GANcon: Protein Contact Map Prediction With Deep Generative Adversarial Network
by: Hang Yang, et al.
Published: (2020-01-01)

Dairy Goat Image Generation Based on Improved-Self-Attention Generative Adversarial Networks
by: Huan Li, et al.
Published: (2020-01-01)

Generative adversarial network based data augmentation to improve cervical cell classification model
by: Suxiang Yu, et al.
Published: (2021-04-01)

Latent-Space-Level Image Anonymization With Adversarial Protector Networks
by: Taehoon Kim, et al.
Published: (2019-01-01)

Generative Adversarial Network and Its Research Progress in Image Generation
by: MA Yongjie, XU Xiaodong, ZHANG Ru, XIE Yirong, CHEN Hong
Published: (2021-10-01)

Semi-Supervised Generative Adversarial Nets with Multiple Generators for SAR Image Recognition
by: Fei Gao, et al.
Published: (2018-08-01)

Using Vehicle Synthesis Generative Adversarial Networks to Improve Vehicle Detection in Remote Sensing Images
by: Kun Zheng, et al.
Published: (2019-09-01)

Methods for Generative Adversarial Output Enhancement
by: Brodie, Michael B.
Published: (2020)

Cannot write session to /tmp/vufind_sessions/sess_vd4vrokirm11ln6tuokcfc2tei