Essays about: "Fréchet Inception Distance"

Showing result 1 - 5 of 14 essays containing the words Fréchet Inception Distance.

  1. 1. Generating Synthetic CT Images Using Diffusion Models

    University essay from Umeå universitet/Institutionen för fysik

    Author : Salih Saleh; [2023]
    Keywords : Machine learning; artificial intelligence; generative models; diffusion models; MRI; CT; synthetic CT; radiation therapy;

    Abstract : Magnetic resonance (MR) images together with computed tomography (CT) images are used in many medical practices, such as radiation therapy. To capture those images, patients have to undergo two separate scans: one for the MR image, which involves using strong magnetic fields, and one for the CT image which involves using radiation (x-rays). READ MORE

  3. 2. Fingerprint Synthesis Using Deep Generative Models

    University essay from Lunds universitet/Matematik LTH

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

    Abstract : 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. READ MORE

  4. 3. An empirical comparison of generative capabilities of GAN vs VAE

    University essay from KTH/Datavetenskap

    Author : Norma Cristina Cueto Ceilis; Hanna Peters; [2022]
    Keywords : ;

    Abstract : Generative models are a family of machine learning algorithms that are aspire to enable computers to understand the real world. Their capability to understand the underlying distribution of data enables them to generate synthetic data from the data they are trained on. READ MORE

  5. 4. Analyzing the Negative Log-Likelihood Loss in Generative Modeling

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Aleix Espuña I Fontcuberta; [2022]
    Keywords : Generative modeling; Normalizing flows; Generative Adversarial Networks; MaximumLikelihood Estimation; Real Non-Volume Preserving flow; Fréchet Inception Distance; Misspecification; Generativa metoder; Normalizing flows; Generative adversarial networks; Maximum likelihood-metoden; Real non-volume preserving flow; Fréchet inception distance; felspecificerade modeller;

    Abstract : Maximum-Likelihood Estimation (MLE) is a classic model-fitting method from probability theory. However, it has been argued repeatedly that MLE is inappropriate for synthesis applications, since its priorities are at odds with important principles of human perception, and that, e.g. READ MORE

  6. 5. High Resolution Quality Enhancement of Digitized Artwork using Generative Adversarial Networks

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Dennis Magnusson; [2022]
    Keywords : Image enhancement; Image style transfer; Image superresolution; Machine Learning; Bildförbättring; Bildstilöversättning; Bildsuperupplösning; Maskininlärning;

    Abstract : Digitization of physical artwork is usually done using image scanning devices in order to ensure that the output is accurate in terms of color and is of sufficiently high resolution, usually over 300 pixels per inch, however the usage of such a device is in some cases unfeasible due to medium or size constraints. Photography of the artwork is another method of artwork digitization, however such methods often produce results containing camera artifacts such as shadows, reflections or low resolution. READ MORE