Sökning: "supervised variational autoencoder"

Visar resultat 1 - 5 av 11 uppsatser innehållade orden supervised variational autoencoder.

  1. 1. Predicting tumour growth-driving interactions from transcriptomic data using machine learning

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Neuroonkologi och neurodegeneration

    Författare :Mathilda Stigenberg; [2023]
    Nyckelord :cancer; immunology; cell-cell interactions; deep learning; variational autoencoder; supervised variational autoencoder; tumour microenvironment; single-cell RNA sequencing; spatial transcriptomics; breast cancer; machine learning;

    Sammanfattning : The mortality rate is high for cancer patients and treatments are only efficient in a fraction of patients. To be able to cure more patients, new treatments need to be invented. Immunotherapy activates the immune system to fight against cancer and one treatment targets immune checkpoints. LÄS MER

  3. 2. Fault Detection and Diagnosis for Automotive Camera using Unsupervised Learning

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

    Författare :Ziyou Li; [2023]
    Nyckelord :Unsupervised Learning; Autoencoders; Image Clustering; Fault Detection and Diagnosis; Morphological Operations; Hardware-in-Loop; Advanced DriverAssistance System; Oövervakad inlärning; Autoencoders; Bildklustering; Felfindning och Diagnostik; Morfologiska Operationer; Hardware-in-Loop; Avancerade Förarassistanssystem;

    Sammanfattning : This thesis aims to investigate a fault detection and diagnosis system for automotive cameras using unsupervised learning. 1) Can a front-looking wide-angle camera image dataset be created using Hardware-in-Loop (HIL) simulations? 2) Can an Adversarial Autoencoder (AAE) based unsupervised camera fault detection and diagnosis method be crafted for SPA2 Vehicle Control Unit (VCU) using an image dataset created using Hardware-inLoop? 3) Does using AAE surpass the performance of using Variational Autoencoder (VAE) for the unsupervised automotive camera fault diagnosis model? In the field of camera fault studies, automotive cameras stand out for its complex operational context, particularly in Advanced Driver-Assistance Systems (ADAS) applications. LÄS MER

  4. 3. Improving Change Point Detection Using Self-Supervised VAEs : A Study on Distance Metrics and Hyperparameters in Time Series Analysis

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

    Författare :Daniel Workinn; [2023]
    Nyckelord :Change point detection; Time series data; Segmentation; Machine learning; Data mining; Detektion av brytpunkter; Tidsseriedata; Segmentering; Maskininlärning; Datautvinning;

    Sammanfattning : This thesis addresses the optimization of the Variational Autoencoder-based Change Point Detection (VAE-CP) approach in time series analysis, a vital component in data-driven decision making. We evaluate the impact of various distance metrics and hyperparameters on the model’s performance using a systematic exploration and robustness testing on diverse real-world datasets. LÄS MER

  5. 4. Prediction of Persistence to Treatment for Patients with Rheumatoid Arthritis using Deep Learning

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

    Författare :Serkan Arda Yilal; [2023]
    Nyckelord :Variational Autoencoders; Rheumatoid Arthritis; Precision Medicine; Treatment Prediction; Deep Learning; Supervised Learning; Rheumatoid Artrit; Precisionsmedicin; Behandlingsförutsägelse; Djupinlärning; Övervakat lärande;

    Sammanfattning : Rheumatoid Arthritis is an inflammatory joint disease that is one of the most common autoimmune diseases in the world. The treatment usually starts with a first-line treatment called Methotrexate, but it is often insufficient. One of the most common second-line treatments is Tumor Necrosis Factor inhibitors (TNFi). LÄS MER

  7. 5. Insurance Fraud Detection using Unsupervised Sequential Anomaly Detection

    Master-uppsats, Linköpings universitet/Institutionen för datavetenskap

    Författare :Anton Hansson; Hugo Cedervall; [2022]
    Nyckelord :Insurance Fraud Detection; Anomaly Detection; Long Short-Term Memory Networks LSTM ; Unsupervised Learning; Autoencoder AE ; Variational Autoencoder VAE ; Interpretable Machine Learning; Feature Engineering; Feature Selection; Feature Importance;

    Sammanfattning : Fraud is a common crime within the insurance industry, and insurance companies want to quickly identify fraudulent claimants as they often result in higher premiums for honest customers. Due to the digital transformation where the sheer volume and complexity of available data has grown, manual fraud detection is no longer suitable. LÄS MER