Sökning: "out-of-distribution detection"

Visar resultat 1 - 5 av 11 uppsatser innehållade orden out-of-distribution detection.

  1. 1. Uncertainty Quantification in Deep Learning for Breast Cancer Classification in Point-of-Care Ultrasound Imaging

    Master-uppsats, Lunds universitet/Matematik LTH

    Författare :Marisa Wodrich; [2024]
    Nyckelord :Uncertainty quantification; Deep learning; Breast cancer classification; Trustworthy AI; Point-of-care ultrasound; Mathematics and Statistics;

    Sammanfattning : Breast cancer is the most common type of cancer worldwide with an estimate of 2.3 million new cases in 2020, and the number one cause of cancer-related deaths in women. LÄS MER

  3. 2. Automated Interpretation of Lung Ultrasound for COVID-19 and Tuberculosis diagnosis

    Master-uppsats, Lunds universitet/Matematik LTH

    Författare :Chloé Soormally; [2023]
    Nyckelord :Tuberculosis; COVID-19; Lung Ultrasound; Computer-aided detection CAD ; Deep learning; Technology and Engineering;

    Sammanfattning : BACKGROUND. Early and accurate detection of infectious respiratory diseases like COVID-19 and tuberculosis (TB) plays a crucial role in effective management and the reduction of preventable mortality. LÄS MER

  4. 3. Dataset Drift in Radar Warning Receivers : Out-of-Distribution Detection for Radar Emitter Classification using an RNN-based Deep Ensemble

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

    Författare :Kevin Coleman; [2023]
    Nyckelord :Radar Emitter Classification; Pulse Descriptor Word; Out of Distribution Detection; Dataset Drift; Uncertainty Estimation; Deep Ensembles; Recurrent Neural Networks; LSTM;

    Sammanfattning : Changes to the signal environment of a radar warning receiver (RWR) over time through dataset drift can negatively affect a machine learning (ML) model, deployed for radar emitter classification (REC). The training data comes from a simulator at Saab AB, in the form of pulsed radar in a time-series. LÄS MER

  5. 4. Detecting Images Outside Training Distribution for Fingerprint Spoof Detection

    Master-uppsats, Lunds universitet/Matematik LTH

    Författare :Daniel Holmkvist; [2023]
    Nyckelord :Machine learning; Out-of-Distribution; Deep Neural Network; spoof detection; Neural Network; Mathematics and Statistics;

    Sammanfattning : Artificial neural networks are known to run into issues when given samples that deviate from the training distribution, where the network may confidently provide an incorrect answer. Out-of-distribution detection methods aims to provide a solution to this issue, by detecting data that deviates from the distribution used to train the model. LÄS MER

  7. 5. Diffusion models for anomaly detection in digital pathology

    Magister-uppsats, Linköpings universitet/Medie- och Informationsteknik; Linköpings universitet/Tekniska fakulteten

    Författare :Ruben Bromée; [2023]
    Nyckelord :out-of-distribution detection; digital pathology data; latent diffusion model; machine learning; neural network; pathology;

    Sammanfattning : Challenges within the field of pathology leads to a high workload for pathologists. Machine learning has the ability to assist pathologists in their daily work and has shown good performance in a research setting. LÄS MER