Sökning: "realworld"

Visar resultat 1 - 5 av 14 uppsatser innehållade ordet realworld.

  1. 1. Bridging Sim-to-Real Gap in Offline Reinforcement Learning for Antenna Tilt Control in Cellular Networks

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

    Författare :Mayank Gulati; [2021]
    Nyckelord :reinforcement learning; transfer learning; simulation-to-reality; simulator; realworld; real-world network data; remote electrical tilt optimization; cellular networks; antenna tilt; network optimization.;

    Sammanfattning : Antenna tilt is the angle subtended by the radiation beam and horizontal plane. This angle plays a vital role in determining the coverage and the interference of the network with neighbouring cells and adjacent base stations. LÄS MER

  2. 2. Detektering av phishing : En litteraturstudie om automatisk detektering av phishing med artificiell intelligens (AI)

    Kandidat-uppsats, Högskolan i Skövde/Institutionen för informationsteknologi

    Författare :Haydar Ameri; [2020]
    Nyckelord :Artificial intelligence; phishing; classification; mail; URL; Artificiell intelligens; phishing; klassificering; mail; URL;

    Sammanfattning : Det ökade antalet mejlanvändare idag har lett till en upptrappning och ytterligare problem som är relaterade till phishing. Phishing är ett stort samhällsproblem idag som drabbar både individer och organisationer. Sedan den första attacken kom 1996, verkar phishing vara ett olöst mysterium än idag. LÄS MER

  3. 3. Unsupervised Learning of Useful and Interpretable Representations from Image Data

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

    Författare :Thomas Gaddy; [2019]
    Nyckelord :;

    Sammanfattning : This master thesis tackles the problem of unsupervised learning of useful and interpretable representations from image data using deep Convolutional Neural Networks (CNN). Recent years have seen remarkable success from using deep learning technologies to tackle computer vision problems. LÄS MER

  4. 4. Federated Learning for Time Series Forecasting Using LSTM Networks: Exploiting Similarities Through Clustering

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

    Författare :Fernando Díaz González; [2019]
    Nyckelord :Federated Learning; Time Series Forecasting; Clustering; Time Series Feature Extraction; Recurrent Neural Networks; Long Short-Term Memory;

    Sammanfattning : Federated learning poses a statistical challenge when training on highly heterogeneous sequence data. For example, time-series telecom data collected over long intervals regularly shows mixed fluctuations and patterns. LÄS MER

  5. 5. Unsupervised Anomaly Detection on Multi-Process Event Time Series

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

    Författare :Nicoló Vendramin; [2018]
    Nyckelord :Anomaly Detection; Recurrent Neural Networks; Time Series Analysis; Unsupervised Learning; Anomalitetsdetektering; Återkommande neurala nätverk; Tidsserieanalys; Oövervakat lärande;

    Sammanfattning : Establishing whether the observed data are anomalous or not is an important task that has been widely investigated in literature, and it becomes an even more complex problem if combined with high dimensional representations and multiple sources independently generating the patterns to be analyzed. The work presented in this master thesis employs a data-driven pipeline for the definition of a recurrent auto-encoder architecture to analyze, in an unsupervised fashion, high-dimensional event time-series generated by multiple and variable processes interacting with a system. LÄS MER