Sökning: "neural data"

Visar resultat 21 - 25 av 2095 uppsatser innehållade orden neural data.

  1. 21. Using Neural Radiance Fields and Gaussian Splatting for 3D reconstruction of aircraft inspections

    Master-uppsats, Lunds universitet/Matematik LTH

    Författare :Roos Eline Bottema; [2024]
    Nyckelord :Technology and Engineering;

    Sammanfattning : The rapid evolution of machine learning techniques has revolutionized computer vision, particularly with the introduction of Neural Radiance Fields (NeRF) and the optimization of 3D Gaussians for rendering novel scene views. These methods, such as NeRF and Gaussian Splatting, have demonstrated success in synthetic data scenarios with consistent lighting and well-captured scenes. LÄS MER

  3. 22. Classifying femur fractures using federated learning

    Master-uppsats, Linköpings universitet/Statistik och maskininlärning

    Författare :Hong Zhang; [2024]
    Nyckelord :Atypical femur fracture; Federated Learning; Neural Network; Classification;

    Sammanfattning : The rarity and subtle radiographic features of atypical femoral fractures (AFF) make it difficult to distinguish radiologically from normal femoral fractures (NFF). Compared with NFF, AFF has subtle radiological features and is associated with the long-term use of bisphosphonates for the treatment of osteoporosis. LÄS MER

  4. 23. The Impact of Deep Neural Network Pruning on the Hyperparameter Performance Space: An Empirical Study

    Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

    Författare :Jonna Matthiesen; [2023-10-24]
    Nyckelord :Compression; Deep Learning; DNN; Hyperparameters; Optimization; Pruning; Hyperparameter Optimisation; Hyperparameter Tuning;

    Sammanfattning : With the continued growth of deep learning models in terms of size and computational requirements, the need for efficient models for deployment on resource-constrained devices becomes crucial. Structured pruning has emerged as a proven method to speed up models and reduce computational requirements. LÄS MER

  5. 24. Machine learning for molecular property prediction and drug safety

    Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

    Författare :Kinga Jenei; [2023-10-23]
    Nyckelord :Molecular property prediction; Acid dissociation constant; pKa; Machine learning; Graph Neural Networks; Molecular descriptors; Drug Discovery;

    Sammanfattning : Utilizing machine learning methods for the prediction of acid dissociation (pKa ) values of compounds holds great significance, as pKa is an important parameter, optimized frequently in drug discovery. Accurate prediction of pKa values could potentially provide valuable insights on other molecular properties and thereby support compound design. LÄS MER

  7. 25. Improving echocardiogram view classification using diffusion models

    Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

    Författare :Luis Arevalo; Anouka Ranby; [2023-10-23]
    Nyckelord :Computer; science; computer science; engineering; project; artificial intelligence; machine learning; deep neural networks; diffusion models; synthetic data; echocardiogram classification;

    Sammanfattning : In the field of medical science datasets are often highly imbalanced, where rare datapoints are of high importance. This study aims to explore the usage of synthetic datasets to improve the classification of echocardiogram views. LÄS MER