Sökning: "Iterative algorithm"

Visar resultat 1 - 5 av 157 uppsatser innehållade orden Iterative algorithm.

  1. 1. Enhancement of a Power Line Information System by Combining BIM and LiDAR Data

    Master-uppsats, KTH/Lantmäteri – fastighetsvetenskap och geodesi

    Författare :Daniel Wollberg; [2024]
    Nyckelord :GIS; BIM; FME; CloudCompare; GIS; BIM; FME; CloudCompare;

    Sammanfattning : With the great ongoing energy transition in Sweden, Svenska Kraftnät (SVK) sees a huge need for investment in the Swedish transmission network and supporting IT- systems.  SVK has a great amount of collected laser data over the electric power transmission network however this data does not contain any semantic attribution that can be analyzed on broader information systems. LÄS MER

  3. 2. Log Frequency Analysis for Anomaly Detection in Cloud Environments

    Master-uppsats, Blekinge Tekniska Högskola/Institutionen för programvaruteknik

    Författare :Prathyusha Bendapudi; [2024]
    Nyckelord :Log Analysis; Log Frequency Patterns; anomaly detection; machine learning; cloud environments;

    Sammanfattning : Background: Log analysis has been proven to be highly beneficial in monitoring system behaviour, detecting errors and anomalies, and predicting future trends in systems and applications. However, with continuous evolution of these systems and applications, the amount of log data generated on a timely basis is increasing rapidly. LÄS MER

  4. 3. Effectiveness of Iterative Algorithms for Recovering Phase in the Presence of Noise for Coherent Diffractive Imaging

    Master-uppsats, Göteborgs universitet / Institutionen för fysik

    Författare :Henry Wittler; [2023-11-29]
    Nyckelord :;

    Sammanfattning : Methods of coherent diffractive imaging (CDI) rely on iterative algorithms to reconstruct the complex exit-surface wave (ESW) of the object being imaged from the measured diffraction intensity only. In this thesis we investigate by simulation the artifacts on reconstruction when noise are present in the measurement. LÄS MER

  5. 4. Over-the-Air Federated Learning with Compressed Sensing

    Master-uppsats, Linköpings universitet/Kommunikationssystem

    Författare :Adrian Edin; [2023]
    Nyckelord :machine learning; ML; Federated Learning; FL; Over-the-air; Over-the-air computation; OtA; OtA computation; AirComp; Compressed sensing; CS; Iterative Hard thresholding; IHT;

    Sammanfattning : The rapid progress with machine learning (ML) technology has solved previously unsolved problems, but training these ML models requires ever larger datasets and increasing amounts of computational resources. One potential solution is to enable parallelization of the computations and allow local processing of training data in distributed nodes, such as Federated Learning (FL). LÄS MER

  7. 5. Point Cloud Registration using both Machine Learning and Non-learning Methods : with Data from a Photon-counting LIDAR Sensor

    Master-uppsats, Linköpings universitet/Datorseende

    Författare :Maja Boström; [2023]
    Nyckelord :Point Cloud Registration; Machine Learning; Photon-counting LIDAR; Iterative Closest Point;

    Sammanfattning : Point Cloud Registration with data measured from a photon-counting LIDAR sensor from a large distance (500 m - 1.5 km) is an expanding field. Data measuredfrom far is sparse and have low detail, which can make the registration processdifficult, and registering this type of data is fairly unexplored. LÄS MER