Sökning: "generative adversarial learning"

Visar resultat 1 - 5 av 13 uppsatser innehållade orden generative adversarial learning.

  1. 1. Object Detection using deep learning and synthetic data

    Master-uppsats, Linköpings universitet/Medie- och InformationsteknikLinköpings universitet/Tekniska fakulteten

    Författare :Love Lidberg; [2018]
    Nyckelord :Deep Learning; Convolutional Neural Networks; Generative Adversarial Networks; Synthetic; Object Detection; Classification;

    Sammanfattning : This thesis investigates how synthetic data can be utilized when training convolutional neural networks to detect flags with threatening symbols. The synthetic data used in this thesis consisted of rendered 3D flags with different textures and flags cut out from real images. LÄS MER

  2. 2. Generation of Synthetic Images with Generative Adversarial Networks

    Master-uppsats, Blekinge Tekniska Högskola/Institutionen för datalogi och datorsystemteknik

    Författare :Mousa Zeid Baker; [2018]
    Nyckelord :classification; deep learning; generative adversarial network; machine learning;

    Sammanfattning : Machine Learning is a fast growing area that revolutionizes computer programs by providing systems with the ability to automatically learn and improve from experience. In most cases, the training process begins with extracting patterns from data. The data is a key factor for machine learning algorithms, without data the algorithms will not work. LÄS MER

  3. 3. Augmenting High-Dimensional Data with Deep Generative Models

    Master-uppsats, KTH/Robotik, perception och lärande, RPL

    Författare :Mårten Nilsson; [2018]
    Nyckelord :GAN; GANs; machine learning; deep learning; generative model; generative models; deep generative model; deep generative models; generative adversarial networks; VAE; VAEs; variational autoencoder; variational autoencoders; autoencoder; auto encoder; encoder; decoder; computer vision; eye tracking; pupil localization; pupil; eyes; eye; synthetic data; big data; data generation; synthetic data generation; neural networks; neural network; high-dimensional data; high-resolution images.;

    Sammanfattning : Data augmentation is a technique that can be performed in various ways to improve the training of discriminative models. The recent developments in deep generative models offer new ways of augmenting existing data sets. LÄS MER

  4. 4. Cell Image Transformation Using Deep Learning

    Master-uppsats, Lunds universitet/Matematik LTH

    Författare :Emmy Sjöstrand; Jesper Jönsson; [2018]
    Nyckelord :Mathematics and Statistics;

    Sammanfattning : This thesis was written at CellaVision who sells digital microscope systems, mainly used for blood analysis. Blood tests are an important part of modern health care and today digital microscopes are widely used to replace conventional microscopy. LÄS MER

  5. 5. Reconstruction and recommendation of realistic 3D models using cGANs

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

    Författare :Mónica Villanueva Aylagas; [2018]
    Nyckelord :Deep Learning; GANs; 3D;

    Sammanfattning : Three-dimensional modeling is the process of creating a representation of a surface or object in three dimensions via a specialized software where the modeler scans a real-world object into a point cloud, creates a completely new surface or edits the selected representation. This process can be challenging due to factors like the complexity of the 3D creation software or the number of dimensions in play. LÄS MER

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