Sökning: "classification"

Visar resultat 21 - 25 av 4326 uppsatser innehållade ordet classification.

  1. 21. Using GIS and satellite data to assess access of green area for children living in growing cities

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

    Författare :Rebecca Borg; [2024]
    Nyckelord :Geography; GIS; Geographical Information System; Urban green space; children; schools; Malmö; Earth and Environmental Sciences;

    Sammanfattning : Urban green space (UGS) refers to open spaces within an urban context that are filled with greenery and nature. These can range from very small vegetation to expansive park areas. The common denominator is that they have proven to be beneficial for human health and well-being. Access to green spaces is also important for children. LÄS MER

  3. 22. Decision Trees for Classification of Repeated Measurements

    Kandidat-uppsats, Linköpings universitet/Tillämpad matematik; Linköpings universitet/Tekniska fakulteten

    Författare :Julianna Holmberg; [2024]
    Nyckelord :Repeated Measurement Data; Growth Curve Model; Linear Discriminant Analysis; Decision Tree; Bootstrap Aggregating; CART; CART-LC;

    Sammanfattning : Classification of data from repeated measurements is useful in various disciplines, for example that of medicine. This thesis explores how classification trees (CART) can be used for classifying repeated measures data. LÄS MER

  4. 23. Self-Supervised Learning for Tabular Data: Analysing VIME and introducing Mix Encoder

    Kandidat-uppsats, Lunds universitet/Fysiska institutionen

    Författare :Max Svensson; [2024]
    Nyckelord :Machine Learning; Self-supervised learning; AI; Physics; Medicine; Physics and Astronomy;

    Sammanfattning : We introduce Mix Encoder, a novel self-supervised learning framework for deep tabular data models based on Mixup [1]. Mix Encoder uses linear interpolations of samples with associated pretext tasks to form useful pre-trained representations. LÄS MER

  5. 24. Measuring the Utility of Synthetic Data : An Empirical Evaluation of Population Fidelity Measures as Indicators of Synthetic Data Utility in Classification Tasks

    Master-uppsats, Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)

    Författare :Alexander Florean; [2024]
    Nyckelord :Synthetic Data; Machine Learning; Population Fidelity Measures; Utility Metrics; Synthetic Data Quality Evaluation; Classification Algorithms; Utility Estimation; Data Privacy; Artificial Intelligence; Experiment Framework; Model Performance Assessment; Syntetisk Data; Maskininlärning; Population Fidelity Mätvärden; Användbarhetsmätvärden; Kvalitetsutvärdering av Syntetisk Data; Klassificeringsalgoritmer; Användbarhetsutvärdering; Dataintegritet; Artificiell Intelligens; AI; Experiment Ramverk; Utvärdering av Modellprestanda;

    Sammanfattning : In the era of data-driven decision-making and innovation, synthetic data serves as a promising tool that bridges the need for vast datasets in machine learning (ML) and the imperative necessity of data privacy. By simulating real-world data while preserving privacy, synthetic data generators have become more prevalent instruments in AI and ML development. LÄS MER

  7. 25. AI-based image generation: The impact of fine-tuning on fake image detection

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

    Författare :Nick Hagström; Anders Rydberg; [2024]
    Nyckelord :Fake image detection; LoRA; DreamBooth; Stable Diffusion; Image generation;

    Sammanfattning : Machine learning-based image generation models such as Stable Diffusion are now capable of generating synthetic images that are difficult to distinguish from real images, which gives rise to a number of legal and ethical concerns. As a potential measure of mitigation, it is possible to train neural networks to detect the digital artifacts present in the images synthesized by many generative models. LÄS MER