Sökning: "synthetic data generation"

Visar resultat 21 - 25 av 84 uppsatser innehållade orden synthetic data generation.

  1. 21. Impact of MR training data on the quality of synthetic CT generation

    Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för fysik

    Författare :Gustav Jönsson; [2022]
    Nyckelord :Generative adversarial network; Machine learning; Radiotherapy; Synthetic CT; MR; CT;

    Sammanfattning : Both computed tomography (CT) and magnetic resonance imaging (MRI) have a purpose for radiotherapy. But having two imaging sessions brings uncertainty which makes it beneficial to create synthetic CT (sCT) images from MR images. In this work a Generative Adversarial Network (GAN) was designed and implemented for sCT generation. LÄS MER

  3. 22. Super-Resolution Vehicle Trajectory using Recurrent Time Series Imputation

    Master-uppsats, Uppsala universitet/Institutionen för informationsteknologi

    Författare :Hasnain Roopawalla; [2022]
    Nyckelord :;

    Sammanfattning : Vehicle data finds its use in a variety of applications in the fields of machine learning and data analysis. The volume of available data is limited by the frequency of data collection, and for several reasons, it can be infeasible to simply amplify this frequency. LÄS MER

  4. 23. Geospatial Trip Data Generation Using Deep Neural Networks

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Aditya Deepak Udapudi; [2022]
    Nyckelord :Deep Learning; Geospatial; Generative Adversarial Network GAN ; Deep Learning; Geospatial; Generativa Motståndsnätverk GAN ;

    Sammanfattning : Development of deep learning methods is dependent majorly on availability of large amounts of high quality data. To tackle the problem of data scarcity one of the workarounds is to generate synthetic data using deep learning methods. LÄS MER

  5. 24. Generating Geospatial Trip DataUsing Deep Neural Networks

    Master-uppsats, Linköpings universitet/Statistik och maskininlärning

    Författare :Ahmed Alhasan; [2022]
    Nyckelord :Deep Learning; Machine Learning; Statistics; Generative Adversarial Networks; Computer Science; Generative Models;

    Sammanfattning : Synthetic data provides a good alternative to real data when the latter is not sufficientor limited by privacy requirements. In spatio-temporal applications, generating syntheticdata is generally more complex due to the existence of both spatial and temporal dependencies. LÄS MER

  7. 25. Geospatial Timeseries Imputation using Deep Neural Networks

    Master-uppsats, Uppsala universitet/Institutionen för informationsteknologi

    Författare :Mattis Kienmayer; [2022]
    Nyckelord :;

    Sammanfattning : With the advancement of technology, data collection has become a big part of many industries.Large amounts of data can be used for analytics purposes, and give companies the opportunityto offer a wider range of services to their customers. LÄS MER