Sökning: "Deep Learning"

Visar resultat 1 - 5 av 1056 uppsatser innehållade orden Deep Learning.

  1. 1. Sequential Anomaly Detection for Log Data Using Deep Learning

    Master-uppsats, Göteborgs universitet/Institutionen för matematiska vetenskaper

    Författare :Lina Hammargren; Wei Wu; [2021-06-14]
    Nyckelord :anomaly detection; recurrent neural network; long short-term memory; semi-supervised learning; seq2seq; transformer; unsupervised learning; log analysis;

    Sammanfattning : AbstractSoftware development with continuous integration changes needs frequent testing forassessment. Analyzing the test output manually is time-consuming and automatingthis process could be beneficial to an organization. LÄS MER

  2. 2. Application of Machine Learning Algorithms for Post Processing of Reference Sensors

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

    Författare :VASILIKI LAMPROUSI; [2021-04-01]
    Nyckelord :Object detection; machine learning; camera; sensors; semi-supervised learning;

    Sammanfattning : The Autonomous Drive (AD) systems and Advanced Driver Assistance Systems(ADAS) in the current and future generations of vehicles include a large numberof sensors which are used to perceive the vehicle’s surroundings. The productionsensors of these vehicles are verified and validated against reference data that areoriginated from high-accurate reference sensors that are placed in a reference roofbox at the top of the vehicle. LÄS MER

  3. 3. Option Modelling by Deep Learning

    Kandidat-uppsats, Göteborgs universitet/Institutionen för nationalekonomi med statistik

    Författare :Niclas Klausson; Victor Tisell; [2021-02-10]
    Nyckelord :Deep learning; deep hedging; generative adversial networks; arbitrage pricing;

    Sammanfattning : In this thesis we aim to provide a fully data driven approach for modelling financial derivatives, exclusively using deep learning. In order for a derivatives model to be plausible, it should adhere to the principle of no-arbitrage which has profound consequences on both pricing and risk management. LÄS MER

  4. 4. Detecting Slag Formation with Deep Learning Methods : An experimental study of different deep learning image segmentation models

    Master-uppsats, Linköpings universitet/Datorseende

    Författare :Christian von Koch; William Anzén; [2021]
    Nyckelord :deep learning; deep neural network; computer vision; image segmentation; iron ore pelletising plant; furnace slag-detection; U-Net; PSPNet;

    Sammanfattning : Image segmentation through neural networks and deep learning have, in the recent decade, become a successful tool for automated decision-making. For Luossavaara-Kiirunavaara Aktiebolag (LKAB), this means identifying the amount of slag inside a furnace through computer vision. LÄS MER

  5. 5. 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