Sökning: "Probabilistic Models"

Visar resultat 1 - 5 av 127 uppsatser innehållade orden Probabilistic Models.

  1. 1. Modelling Long Term Memory in the Bayesian Confidence Neural Network Model

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

    Författare :Charu Karn; Samir Samahunov; [2023]
    Nyckelord :;

    Sammanfattning : Memory is a fascinating and complex part of human life. Understanding memory and simulating itthrough modelling can help society take steps towards understanding health issues such asAlzheimer's, dementia and amnesia. LÄS MER

  3. 2. Clinical Assessment of Deep Learning-Based Uncertainty Maps in Lung Cancer Segmentation

    Master-uppsats, KTH/Skolan för kemi, bioteknologi och hälsa (CBH)

    Författare :Federica Carmen Maruccio; [2023]
    Nyckelord :3D U-Net; Contouring; Clinical validation; Deep learning; Lung cancer; Monte Carlo dropout; Probability map; Reliability diagram; Segmentation; Uncertainty map;

    Sammanfattning : Prior to radiation therapy planning, tumours and organs at risk need to be delineated. In recent years, deep learning models have opened the possibility of automating the contouring process, speeding up the procedures and helping clinicians. LÄS MER

  4. 3. Generation of Synthetic Traffic Sign Images using Diffusion Models

    Master-uppsats, Linköpings universitet/Datorseende

    Författare :Johanna Carlson; Lovisa Byman; [2023]
    Nyckelord :Machine Learning; Computer Vision; Diffusion Models; Traffic Sign Recognition; Traffic Sign Classification; Synthetic Data; Maskininlärning; Datorseende; Diffusionsmodeller; Trafikskyltsigenkänning; Trafikskyltsklassificering; Syntetisk data;

    Sammanfattning : In the area of Traffic Sign Recognition (TSR), deep learning models are trained to detect and classify images of traffic signs. The amount of data available to train these models is often limited, and collecting more data is time-consuming and expensive. LÄS MER

  5. 4. Text to Music Audio Generation using Latent Diffusion Model : A re-engineering of AudioLDM Model

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

    Författare :Ernan Wang; [2023]
    Nyckelord :Text to Music Audio Generation; Latent Diffusion; AudioLDM; Sampling Methods; Denoising Diffusion Probabilistic Model DDPM ; Denoising Diffusion Implicit Model DDIM ; Text till musik Ljudgenerering; Latent Diffusion; AudioLDM; Samplingsmetoder; DDPM; DDIM;

    Sammanfattning : In the emerging field of audio generation using diffusion models, this project pioneers the adaptation of the AudioLDM model framework, initially designed for text-to-daily sounds generation, towards text-to-music audio generation. This shift addresses a gap in the current scope of audio diffusion models, predominantly focused on everyday sounds. LÄS MER

  7. 5. John the Baptist Through the Lens of Generative AI : A Narrative and Reception-Historical Analysis of Mark 1

    Kandidat-uppsats, Uppsala universitet/Teologiska institutionen

    Författare :Daniel Wettervik; [2023]
    Nyckelord :John the Baptist; Gospel of Mark; biblical art; visual exegesis; narrative criticism; Late Ancient Christian Sources; phenomenology; generative artificial intelligence; artificial intelligence; Midjourney; Johannes döparen; Markusevangeliet; biblisk konst; visuell exegetik; narrativ tolkning; patristik; fenomenologi; generativ artificiell intelligens; artificiell intelligens; Midjourney;

    Sammanfattning : This thesis addresses the intersection of reception history in biblical studies, Generative Artificial Intelligence (GAI) and phenomenology. Three images, from text prompts using different English translations of Mark 1:1–8 (KJV, NRSV and NIV) have been generated by GAI. LÄS MER