Sökning: "Simon Maskell"

Hittade 3 avhandlingar innehållade orden Simon Maskell.

  1. 1. Tracking and Planning for Surveillance Applications

    Författare :Per Skoglar; Fredrik Gustafsson; David Törnqvist; Umut Orguner; Simon Maskell; Linköpings universitet; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; target tracking; sensor control; planning; surveillance; vision sensor;

    Sammanfattning : Vision and infrared sensors are very common in surveillance and security applications, and there are numerous examples where a critical infrastructure, e.g. a harbor, an airport, or a military camp, is monitored by video surveillance systems. LÄS MER

  3. 2. Modeling of Magnetic Fields and Extended Objects for Localization Applications

    Författare :Niklas Wahlström; Fredrik Gustafsson; Thomas B. Schön; Simon Maskell; Linköpings universitet; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Localization; magnetic tracking; extended target tracking; signal processing; machine learning; Gaussian processes; deep dynamical model; discretization;

    Sammanfattning : The level of automation in our society is ever increasing. Technologies like self-driving cars, virtual reality, and fully autonomous robots, which all were unimaginable a few decades ago, are realizable today, and will become standard consumer products in the future. LÄS MER

  4. 3. Sequential Monte Carlo methods for conjugate state-space models

    Författare :Anna Wigren; Fredrik Lindsten; Lawrence Murray; Riccardo Sven Risuleo; Simon Maskell; Uppsala universitet; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Sequential Monte Carlo; Particle filter; Markov chain Monte Carlo; Conjugacy; State-space model; Probabilistic programming; Electrical Engineering with specialization in Signal Processing; Elektroteknik med inriktning mot signalbehandling;

    Sammanfattning : Bayesian inference in state-space models requires the solution of high-dimensional integrals, which is intractable in general. A viable alternative is to use sample-based methods, like sequential Monte Carlo, but this introduces variance into the inferred quantities that can sometimes render the estimates useless. LÄS MER