Sökning: "sparse learning"

Visar resultat 16 - 20 av 67 avhandlingar innehållade orden sparse learning.

  1. 16. The PET sampling puzzle : intelligent data sampling methods for positron emission tomography

    Författare :Klara Leffler; Jun Yu; Ida Häggström; Zhiyong Zhou; Saikat Chatterjee; Umeå universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; sparse signal processing; compressed sensing; Poisson denoising; positron emission tomography PET ; sinogram denoising; sinogram inpainting; deep learning; matematisk statistik; Mathematical Statistics;

    Sammanfattning : Much like a backwards computed Sudoku puzzle, starting from the completed number grid and working ones way down to a partially completed grid without damaging the route back to the full unique solution, this thesis tackles the challenges behind setting up a number puzzle in the context of biomedical imaging. By leveraging sparse signal processing theory, we study the means of practical undersampling of positron emission tomography (PET) measurements, an imaging modality in nuclear medicine that visualises functional processes within the body using radioactive tracers. LÄS MER

  3. 17. Unsupervised feature learning applied to condition monitoring

    Författare :Sergio Martín del Campo Barraza; Fredrik Sandin; Kjersti Engan; Luleå tekniska universitet; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Industriell elektronik; Industrial Electronics;

    Sammanfattning : Improving the reliability and efficiency of rotating machinery are central problems in many application domains, such as energy production and transportation. This requires efficient condition monitoring methods, including analytics needed to predict and detect faults and manage the high volume and velocity of data. LÄS MER

  4. 18. Domain Knowledge Assisted Robotic Exploration and Source Localization

    Författare :Thomas Wiedemann; Achim Lilienthal; Dmitriy Shutin; Alcherio Martinoli; Örebro universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Mobile Robot Olfaction; Robotic Exploration; Gas Dispersion Modelling; Bayesian Inference; Sparse Bayesian Learning;

    Sammanfattning : Deploying mobile robots to explore hazardous environments provides an advantageous way to avoid threats for human operators. For example, in situations, where airborne toxic or explosive material is leaking, robots can be dispatched to localize the leaks. LÄS MER

  5. 19. Data-Efficient Reinforcement and Transfer Learning in Robotics

    Författare :Xi Chen; Patric Jensfelt; Ville Kyrki; KTH; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; Computer Science; Datalogi;

    Sammanfattning : In the past few years, deep reinforcement learning (RL) has shown great potential in learning action selection policies for solving different tasks.Despite its impressive success in games, several challenges remain, such as designing appropriate reward functions, collecting large amounts of interactive data, and dealing with unseen cases, which make it difficult to apply RL algorithms to real-world robotics tasks. LÄS MER

  7. 20. Machine Learning Techniques for Enhanced Heat Transfer Modelling

    Författare :Jerol Soibam; Rebei Bel Fdhila; Ioanna Aslanidou; Konstantinos Kyprianidis; Andrea Ianiro; Mälardalens universitet; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Energy- and Environmental Engineering; energi- och miljöteknik;

    Sammanfattning : With the continuous growth of global energy demand, processes from power generation to electronics cooling become vitally important. The role of heat transfer in these processes is crucial, facilitating effective monitoring, control, and optimisation. LÄS MER