Sökning: "semi-supervised learning"

Visar resultat 1 - 5 av 58 uppsatser innehållade orden semi-supervised 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. Style Transfer Paraphrasing for Consistency Training in Sentiment Classification

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

    Författare :Núria Casals; [2021]
    Nyckelord :Semi-Supervised Learning; Data Augmentation; Sentiment Classification; Neural Paraphrasing; Semi-övervakad inlärning; Data förändring; Sentimentklassificering; Neural parafrasering;

    Sammanfattning : Text data is easy to retrieve but often expensive to classify, which is why labeled textual data is a resource often lacking in quantity. However, the use of labeled data is crucial in supervised tasks such as text classification, but semi-supervised learning algorithms have shown that the use of unlabeled data during training has the potential to improve model performance, even in comparison to a fully supervised setting. LÄS MER

  4. 4. Semi-Supervised Adaptive Object Detection for Efficient PrecisionAgriculture

    Uppsats för yrkesexamina på avancerad nivå, Örebro universitet/Institutionen för naturvetenskap och teknik

    Författare :Humam Amouri; [2021]
    Nyckelord :;

    Sammanfattning : Existing supervised learning-based detectors for precision agriculturehave previously achieved high accuracy in challenging classificationtasks. However, their performance deteriorate when presented with new environmentsdue to variations in observed objects and surrounding environment. LÄS MER

  5. 5. Semi-Supervised Training with One-stage Object Detection

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

    Författare :Nancy Xu; [2021]
    Nyckelord :;

    Sammanfattning : Training a specialized object detection model requires large amounts of labeled data that may not be easily obtainable. In contrast, large amounts of unlabeled data relevant to the task are often available. In this report a semi-supervised approach that increases the amount of training data by adding soft labels is examined. LÄS MER