Sökning: "Avvikelsedetektering"

Visar resultat 1 - 5 av 15 uppsatser innehållade ordet Avvikelsedetektering.

  1. 1. Unsupervised Online Anomaly Detection in Multivariate Time-Series

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Datorteknik

    Författare :Ludvig Segerholm; [2023]
    Nyckelord :unsupervised; online; anomaly detection; explainable ai; machine learning; mahalanobis distance;

    Sammanfattning : This research aims to identify a method for unsupervised online anomaly detection in multivariate time series in dynamic systems in general and on the case study of Devwards IoT-system in particular. A requirement of the solution is its explainability, online learning and low computational expense. LÄS MER

  3. 2. Football Trajectory Modeling Using Masked Autoencoders : Using Masked Autoencoder for Anomaly Detection and Correction for Football Trajectories

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

    Författare :Sandra Tor; [2023]
    Nyckelord :Machine Learning; Autoencoders; Masked autoencoders; Time series; Trajectory modeling; Time series modeling; Anomaly detection; Anomaly correction; Football; Maskininlärning; Autoencoders; Maskerade autoencoders; Tidsserie; Banmodellering; Tidsseriemodellering; Avvikelsedetektering; Avvikelsekorrigering; Fotboll;

    Sammanfattning : Football trajectory modeling is a powerful tool for predicting and evaluating the movement of a football and its dynamics. Masked autoencoders are scalable self-supervised learners used for representation learning of partially observable data. LÄS MER

  4. 3. Sign of the Times : Unmasking Deep Learning for Time Series Anomaly Detection

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

    Författare :Daniel Richards Ravi Arputharaj; [2023]
    Nyckelord :Anomaly detection; multivariate time series data; deep learning models; model complexity; resource-constrained systems; Variational Autoencoders VAEs ; Convolutional Variational Autoencoders; evaluation metrics in time series; Anomalidetektering; Multivariata tidsseriedata; Djupinlärningsmodeller; Modellkomplexitet; Resursbegränsade system; Variational Autoencoders VAEs ; Konvolutionella Variational Autoencoders; Utvärderingsmått inom tidsserier;

    Sammanfattning : Time series anomaly detection has been a longstanding area of research with applications across various domains. In recent years, there has been a surge of interest in applying deep learning models to this problem domain. LÄS MER

  5. 4. Selective Kernel Network based Crowding Counting and Crowd Density Estimation

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

    Författare :Jinchen Liu; [2023]
    Nyckelord :Crowding Counting; Convolution Neural Network; Selective kernel; Trängselräkning; konvolutionsneuralnätverk; Selektiv kärna;

    Sammanfattning : Managing crowd density has become an immense challenge for public authorities due to population growth and evolving human dynamics. Crowd counting estimates the number of individuals in a given area or scene, making it a practical technique applicable in real-world scenarios such as surveillance and traffic control. LÄS MER

  7. 5. Digital Twin for Firmware and Artificial Intelligence prototyping

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

    Författare :Gianluca Maragno; [2023]
    Nyckelord :Digital Twin; Industry 4.0; SystemC; MCU; TLM; sensors; MEMS; Machine Learning; Artificial Intelligence; simulations; testing; correct-by-design.; Digital Tvilling; Industri 4.0; SystemC; MCU; TLM; sensorer; MEMS; Maskininlärning; Artificiell Intelligens; simuleringar; testning; korrekt-från-design.;

    Sammanfattning : The forth industrial revolution has risen the born of new mega trends for the improvement of the time to market and the spare of resources in the development and manufacturing of a new product. Among these trends, the Digital Twin (DT) is the one of major interests for developers and strategy analysts. LÄS MER