Sökning: "residual error models"

Visar resultat 1 - 5 av 21 uppsatser innehållade orden residual error models.

  1. 1. Deep learning for temporal super-resolution of 4D Flow MRI

    Master-uppsats, KTH/Matematik (Avd.)

    Författare :Pia Callmer; [2023]
    Nyckelord :Temporal super-resolution; 4D Flow MRI; CNN; Artificial Intelligence; MRI; 4D flow; Temporal superupplösning; 4D flöde MRI; CNN; artificiell intelligens; MRI; 4D-flöde;

    Sammanfattning : The accurate assessment of hemodynamics and its parameters play an important role when diagnosing cardiovascular diseases. In this context, 4D Flow Magnetic Resonance Imaging (4D Flow MRI) is a non-invasive measurement technique that facilitates hemodynamic parameter assessment as well as quantitative and qualitative analysis of three-directional flow over time. LÄS MER

  3. 2. BAGGED PREDICTION ACCURACY IN LINEAR REGRESSION

    Magister-uppsats, Uppsala universitet/Statistiska institutionen

    Författare :Daniel Kimby; [2022]
    Nyckelord :;

    Sammanfattning : Bootstrap aggregation, or bagging, is a prominent method used in statistical inquiry suggested to improve predictive performance. It is useful to confirm the efficacy of such improvements and to expand upon them. LÄS MER

  4. 3. Generation and Detection of Adversarial Attacks in the Power Grid

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen för systemteknik

    Författare :Oscar Larsson; [2022]
    Nyckelord :Machine Learning; Adversarial Learning; Power Systems; State Estimation; Detectability Constraints;

    Sammanfattning : Machine learning models are vulnerable to adversarial attacks that add perturbations to the input data. Here we model and simulate power flow in a power grid test case and generate adversarial attacks for these measurements in three different ways. LÄS MER

  5. 4. Automatic Development of Pharmacokinetic Structural Models

    Master-uppsats, Uppsala universitet/Institutionen för farmaci

    Författare :Alzahra Hamdan; [2022]
    Nyckelord :pharmacometrics; non-linear mixed effects; modelling; pharmacokinetics; NONMEM; automation; exhaustive algorithm; stepwise algorithm; structural models; inter-individual variability; residual error models; model selection;

    Sammanfattning : Introduction: The current development strategy of population pharmacokinetic models is a complex and iterative process that is manually performed by modellers. Such a strategy is time-demanding, subjective, and dependent on the modellers’ experience. LÄS MER

  7. 5. Deep Learning for Dose Prediction in Radiation Therapy : A comparison study of state-of-the-art U-net based architectures

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen för systemteknik

    Författare :Maja Arvola; [2021]
    Nyckelord :Radiotherapy; Machine learning; Dose prediction; U-net;

    Sammanfattning : Machine learning has shown great potential as a step in automating radiotherapy treatment planning. It can be used for dose prediction and a popular deep learning architecture for this purpose is the U-net. Since it was proposed in 2015, several modifications and extensions have been proposed in the literature. LÄS MER