Sökning: "convolutional neural networks"

Visar resultat 1 - 5 av 409 uppsatser innehållade orden convolutional neural networks.

  1. 1. Deep Learning with Importance Sampling for Brain Tumor MR Segmentation

    Master-uppsats, KTH/Optimeringslära och systemteori

    Författare :Hanna Westermark; [2021]
    Nyckelord :Deep learning; importance sampling; segmentation; convolutional neural networks; MRI; brain tumour; Djupinlärning; importance sampling; segmentering; faltningsnätverk; MRI; hjärntumör;

    Sammanfattning : Segmentation of magnetic resonance images is an important part of planning radiotherapy treat-ments for patients with brain tumours but due to the number of images contained within a scan and the level of detail required, manual segmentation is a time consuming task. Convolutional neural networks have been proposed as tools for automated segmentation and shown promising results. LÄS MER

  2. 2. Deep Learning for Iceberg Detection in Satellite Images

    Master-uppsats, Uppsala universitet/Institutionen för informationsteknologi

    Författare :Shuzhi Dong; [2021]
    Nyckelord :;

    Sammanfattning : The application of satellite images for ship and iceberg monitoring is essentialin many ways in Arctic waters. Even though the detection of ships and icebergs in images is well established using Geoscience techniques, the discrimination between those two target classes still represents a challenge for operational scenarios. LÄS MER

  3. 3. Classification of Gear-shift data using machine learning

    Master-uppsats, Mälardalens högskola/Akademin för innovation, design och teknik

    Författare :Daniel Stenekap; [2021]
    Nyckelord :Machine Learning; AI;

    Sammanfattning : Today, automatic transmissions are the industrial standard in heavy-duty vehicles. However, tolerances and component wear can cause factory calibrated gearshifts to have deviations that have a negative impact on clutch durability and driver comfort. LÄS MER

  4. 4. Ensembles of Single Image Super-Resolution Generative Adversarial Networks

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

    Författare :Victor Castillo Araújo; [2021]
    Nyckelord :Generative Adversarial Networks; Single Image Super-Resolution; Computer Vision; Convolutional Neural Networks; Ensemble Learning; Generative Adversarial Networks; Superupplösning; Datorseende; Bildanalys; Convolutional neural networks; Ensembler;

    Sammanfattning : Generative Adversarial Networks have been used to obtain state-of-the-art results for low-level computer vision tasks like single image super-resolution, however, they are notoriously difficult to train due to the instability related to the competing minimax framework. Additionally, traditional ensembling mechanisms cannot be effectively applied with these types of networks due to the resources they require at inference time and the complexity of their architectures. LÄS MER

  5. 5. Group Invariant Convolutional Boltzmann Machines

    Master-uppsats, Göteborgs universitet/Institutionen för matematiska vetenskaper

    Författare :Maria Lindström; [2020-12-04]
    Nyckelord :Convolutional Boltzmann Machines; Convolutional neural networks; artificial neural networks; machine learning; group invariance; group equivariance;

    Sammanfattning : We investigate group invariance in unsupervised learning in the context of certain generative networks based on Boltzmann machines. Specifically, we introduce a generalization of restricted Boltzmann machines which is adapted to input data that is acted upon by any compact group G. LÄS MER