Sökning: "Självövervakad träning"

Hittade 5 uppsatser innehållade orden Självövervakad träning.

  1. 1. Self-supervised pre-training of an attention-based model for 3D medical image segmentation

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

    Författare :Albert Sund Aillet; [2023]
    Nyckelord :Computer vision; Deep learning; 3D Medical image segmentation; Self-supervised learning; Datorseende; Djupinlärning; 3D Medicinsk bildsegmentering; Självövervakad träning;

    Sammanfattning : Accurate segmentation of anatomical structures is crucial for radiation therapy in cancer treatment. Deep learning methods have been demonstrated effective for segmentation of 3D medical images, establishing the current standard. However, they require large amounts of labelled data and suffer from reduced performance on domain shift. LÄS MER

  3. 2. Analysis of Brain Signals from Patients with Parkinson’s Disease using Self-Supervised Learning

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

    Författare :Emma Lind; [2022]
    Nyckelord :Machine Learning; Self-supervised learning; Feature extraction; Parkinson’s Disease; Magnetoencephalography; Electroencephalogram; Maskininlärning; Självlärande inlärning; Särdragsextraktion; Parkinsons sjukdom; Magnetoencefalografi; Elektroencefalografi;

    Sammanfattning : Parkinson’s disease (PD) is one of the most common neurodegenerative brain disorders, commonly diagnosed and monitored via clinical examinations, which can be imprecise and lead to a delayed or inaccurate diagnosis. Therefore, recent research has focused on finding biomarkers by analyzing brain networks’ neural activity to find abnormalities associated with PD pathology. LÄS MER

  4. 3. Unsupervised 3D Human Pose Estimation

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

    Författare :Sri Datta Budaraju; [2021]
    Nyckelord :Computer Vision; Projective Geometry; Deep Learning; Unsupervised Learning; 3D Human Pose Estimation; GAN; AutoEncoder; Hybrid Generative Model; Self Supervision;

    Sammanfattning : The thesis proposes an unsupervised representation learning method to predict 3D human pose from a 2D skeleton via a VAEGAN (Variational Autoencoder Generative Adversarial Network) hybrid network. The method learns to lift poses from 2D to 3D using selfsupervision and adversarial learning techniques. LÄS MER

  5. 4. Transfer learning techniques in time series analysis

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

    Författare :Robinson Sablons de Gélis; [2021]
    Nyckelord :Deep learning; Time series; Transfer learning; Self-supervised learning; Domain adaptation; Djupinlärning; tidsserier; överföringsinlärning; självövervakad inlärning; domänanpassning;

    Sammanfattning : Deep learning works best with vast andd well-distributed data collections. However, collecting and annotating large data sets can be very time-consuming and expensive. Moreover, deep learning is specific to domain knowledge, even with data and computation. E. LÄS MER

  7. 5. Resource-efficient image segmentation using self-supervision and active learning

    Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)

    Författare :Muriel Max; [2021]
    Nyckelord :Image Segmentation; Deep Learning; Active Learning; Self-supervision; Pretraining; Bildsegmentering; Djupinlärning; Active Learning; självövervakad träning; Pre-training;

    Sammanfattning : Neural Networks have been demonstrated to perform well in computer vision tasks, especially in the field of semantic segmentation, where a classification is performed on a per pixel-level. Using deep learning can reduce time and effort in comparison to manual segmentation, however, the performance of neural networks highly depends on the data quality and quantity, which is costly and time-consuming to obtain; especially for image segmentation tasks. LÄS MER