Sökning: "cycleGAN"

Visar resultat 1 - 5 av 23 uppsatser innehållade ordet cycleGAN.

  1. 1. Quality enhancement of time-resolved computed tomography scans with cycleGAN

    Master-uppsats, Lunds universitet/Synkrotronljusfysik; Lunds universitet/Fysiska institutionen

    Författare :Johannes Stubbe; [2023]
    Nyckelord :carbon fibers; carbon fibres; microfibers; tomography; deep learning; cycleGAN; time-resolved tomography; Physics and Astronomy;

    Sammanfattning : Time-resolved x-ray tomography enables us to dynamically and non-destructively study the interior of a specimen. The obtainable temporal resolution is limited by the x-ray flux and the desired spatial resolution. LÄS MER

  3. 2. Using Generative Adversarial Networks for H&E-to-HER2 Stain Translation in Digital Pathology Images

    Master-uppsats, Linköpings universitet/Institutionen för medicinsk teknik

    Författare :William Tirmén; [2023]
    Nyckelord :Machine learning; Artificial intelligence; Digital pathology; Image processing; Generative adversarial networks; Image-to-image translation;

    Sammanfattning : In digital pathology, hematoxylin & eosin (H&E) is a routine stain which is performed on most clinical cases and it often provides clinicians with sufficient information for diagnosis. However, when making decisions on how to guide breast cancer treatment, immunohistochemical staining of human epidermal growth factor 2 (HER2 staining) is also needed. LÄS MER

  4. 3. Domain Adaptation Of Front View Synthetic Point Clouds Using GANs For Autonomous Driving

    Master-uppsats, KTH/Väg- och spårfordon samt konceptuell fordonsdesign

    Författare :Friedemann Kleinsteuber; [2023]
    Nyckelord :LiDAR; Domain Adaptation; GAN; CycleGAN; Simulation; LiDAR; Domänadaption; GAN; CycleGAN; Simulation;

    Sammanfattning : The perception of the environment is one of the main enablers of Autonomous Driving and is driven by Cameras, RADAR, and LiDAR sensors. Deep Learning algorithms used in perception need a vast amount of labeled, high-quality data which is costly to obtain for LiDAR sensors. LÄS MER

  5. 4. Fingerprint Synthesis Using Deep Generative Models

    Master-uppsats, Lunds universitet/Matematik LTH

    Författare :Weizhong Tang; Diego André Figueroa Llamosas; [2023]
    Nyckelord :Fingerprint Synthesis; Deep Generative Models; Style Transfer; Metrics; Technology and Engineering;

    Sammanfattning : The advancements in biometric technology have amplified the need for more robust fingerprint synthesis techniques. In this thesis, we first explored the application of synthesizing normal fingerprint images in high fidelity using deep generative models (e.g. LÄS MER

  7. 5. Genre style transfer : Symbolic genre style transfer utilising GAN with additional genre-enforcing discriminators

    Master-uppsats, Högskolan i Halmstad/Akademin för informationsteknologi

    Författare :Leif Sulaiman; Sebastian Larsson; [2022]
    Nyckelord :Artificial Intelligence; Machine Learning; Deep Learning; Generative Adversarial Network; Variational Autoencoder; CycleGAN; Music; Style Transfer; Neural Network;

    Sammanfattning : Style transfer using Generative adversarial networks (GANs) has been successful in recent publications. One field in style transfer is music style transfer, in which a piece of music is transformed in some way, be it through genre-, harmonic-, rhythmic transfer, etc. LÄS MER