Sökning: "synthetic images"

Visar resultat 1 - 5 av 196 uppsatser innehållade orden synthetic images.

  1. 1. Using NeRF- and Mesh-Based Methods to Improve Visualisation of Point Clouds

    Master-uppsats, Lunds universitet/Matematik LTH

    Författare :Vilma Ylvén; Oscar Montelin; [2024]
    Nyckelord :Technology and Engineering; Mathematics and Statistics;

    Sammanfattning : In recent years, the field of generating synthetic images from novel view points has seen some major improvements. Most importantly with the publication of Neural Radiance Fields allowing for extremely detailed and accurate 3D novel views. LÄS MER

  2. 2. AI-based image generation: The impact of fine-tuning on fake image detection

    Kandidat-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

    Författare :Nick Hagström; Anders Rydberg; [2024]
    Nyckelord :Fake image detection; LoRA; DreamBooth; Stable Diffusion; Image generation;

    Sammanfattning : Machine learning-based image generation models such as Stable Diffusion are now capable of generating synthetic images that are difficult to distinguish from real images, which gives rise to a number of legal and ethical concerns. As a potential measure of mitigation, it is possible to train neural networks to detect the digital artifacts present in the images synthesized by many generative models. LÄS MER

  3. 3. Using Neural Radiance Fields and Gaussian Splatting for 3D reconstruction of aircraft inspections

    Master-uppsats, Lunds universitet/Matematik LTH

    Författare :Roos Eline Bottema; [2024]
    Nyckelord :Technology and Engineering;

    Sammanfattning : The rapid evolution of machine learning techniques has revolutionized computer vision, particularly with the introduction of Neural Radiance Fields (NeRF) and the optimization of 3D Gaussians for rendering novel scene views. These methods, such as NeRF and Gaussian Splatting, have demonstrated success in synthetic data scenarios with consistent lighting and well-captured scenes. LÄS MER

  4. 4. Image Quality Assessment Pipeline and Semi-Automated Annotation method for Synthetic Data

    Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

    Författare :Liam Le Tran; Edina Dedovic; [2023-10-24]
    Nyckelord :Facial Expression Recognition; FACS; Action Units; styleGAN2-ada; synthetic data; Image Quality Assessment; Multi-stage Pre-training; Pipeline Processing; Semi-automated Human Annotation;

    Sammanfattning : Predicting human emotions through facial expression, particularly in relation to medication field such as clinical trial settings, has garnered scientific interest in recent years due to significant understanding of the impact of treatment on emotions and social functioning. This thesis aims to improve performance of a FER model using large scale of synthetic data. LÄS MER

  5. 5. Improving echocardiogram view classification using diffusion models

    Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

    Författare :Luis Arevalo; Anouka Ranby; [2023-10-23]
    Nyckelord :Computer; science; computer science; engineering; project; artificial intelligence; machine learning; deep neural networks; diffusion models; synthetic data; echocardiogram classification;

    Sammanfattning : In the field of medical science datasets are often highly imbalanced, where rare datapoints are of high importance. This study aims to explore the usage of synthetic datasets to improve the classification of echocardiogram views. LÄS MER