Sökning: "Text data augmentation"

Visar resultat 1 - 5 av 16 uppsatser innehållade orden Text data augmentation.

  1. 1. Data Augmentation: Enhancing Named Entity Recognition Performance on Swedish Medical Texts

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

    Författare :Lucas Rosvall; Niklas Paasonen; [2023-10-05]
    Nyckelord :Machine Learning; Information Extraction; Named Entity Recognition; BERT; Data Augmentation;

    Sammanfattning : Named Entity Recognition (NER) refers to the task of locating relevant information within text sequences. Within the medical domain, it can benefit applications such as de-identifying patient records or extracting valuable data for other downstream tasks. LÄS MER

  3. 2. Simulating metal ct artefacts for ground truth generation in deep learning.

    Master-uppsats, Lunds universitet/Avdelningen för Biomedicinsk teknik

    Författare :Arthur Barakat; [2023]
    Nyckelord :Technology and Engineering;

    Sammanfattning : CT scanning stands as one of the most employed imaging techniques used in clinical field. In the presence of metal implants in the field of view (FOV), distortions and noise appear on the 3D image leading to inaccurate bone segmentation, often required for surgery planning or implant design. LÄS MER

  4. 3. Natural Language Processing for Improving Search Query Results : Applied on The Swedish Armed Force's Profession Guide

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Datalogi

    Författare :Andreas Harju Schnee; [2023]
    Nyckelord :natural language processing; NLP; maskininlärning; ML; artificiell intelligens; AI; language model; information retrieval system; document embedding; text representation; text data augmentation;

    Sammanfattning : Text has been the historical way of preserving and acquiring knowledge, and text data today is an increasingly growing part of the digital footprint together with the need to query this data for information. Seeking information is a constant ongoing process, and is a crucial part of many systems all around us. LÄS MER

  5. 4. Motor Imagery Signal Classification using Adversarial Learning - A Systematic Literature Review

    Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

    Författare :Osama Mahmudi; Shubhra Mishra; [2023]
    Nyckelord :Adversarial Learning; Motor Imagery; BCI; EEG; Machine Learning;

    Sammanfattning : Context: Motor Imagery (MI) signal classification is a crucial task for developing Brain-Computer Interfaces (BCIs) that allow people to control devices using their thoughts. However, traditional machine learning approaches often suffer from limited performance due to inter-subject variability and limited data availability. LÄS MER

  7. 5. Automatic text placement on maps using deep learning keypoint detection models

    Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Författare :Azin Khosravi Khorashad; [2022]
    Nyckelord :machine learning; Stacked hourglass networks; attention mechanism; CNN; geomatics; Earth and Environmental Sciences;

    Sammanfattning : Labeling the map is one of the most essential parts of the cartographic process that requires a huge time and energy. It is proven that the automation of map labeling is an NP-hard problem. There have been many research studies that tried to solve it such as rule-based methods, metaheuristics, and integer programming. LÄS MER