Sökning: "Examensarbete självkörande"

Visar resultat 1 - 5 av 25 uppsatser innehållade orden Examensarbete självkörande.

  1. 1. Multi-Scale Task Dynamics in Transfer and Multi-Task Learning : Towards Efficient Perception for Autonomous Driving

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

    Författare :Simon Ekman von Huth; [2023]
    Nyckelord :Autonomous Driving; Computer Vision; Deep Learning; Machine Learning; Multi-Task Learning; Transfer Learning; Task Relationships; Task Dynamics; Python; Multi-Scale Representation Learning; Fuss-Free Network; Självkörande Fordon; Datorseende; Djupinlärning; Maskininlärning; Multiuppgiftsinlärning; Överföringsinlärning; Uppgiftsrelationer; Uppgiftsdynamik; Python; Flerskalig Representationsinlärning; Fuss-Free Nätverk;

    Sammanfattning : Autonomous driving technology has the potential to revolutionize the way we think about transportation and its impact on society. Perceiving the environment is a key aspect of autonomous driving, which involves multiple computer vision tasks. LÄS MER

  3. 2. Parameter Estimation and Simulation of Driving Datasets

    Master-uppsats, KTH/Väg- och spårfordon samt konceptuell fordonsdesign

    Författare :Bojian Qu; [2023]
    Nyckelord :autonomous vehicles; safety assessment; trajectory generation; safety-critical scenarios; density estimation; approximate inference; självkörande fordon; säkerhetsbedömning; bana generering; säkerhetskritiska scenarier; densitetsuppskattning; ungefärlig slutledning;

    Sammanfattning : The development of autonomous driving in recent years has been in full swing and one of the aspects that Autonomous Vehicles (AVs) should always focus on is safety. Although the corresponding technology has gradually matured, and AVs have performed well in a large number of tests, people are still uncertain whether AVs can cope with all possible situations. LÄS MER

  4. 3. Detecting Images Outside Training Distribution for Fingerprint Spoof Detection

    Master-uppsats, Lunds universitet/Matematik LTH

    Författare :Daniel Holmkvist; [2023]
    Nyckelord :Machine learning; Out-of-Distribution; Deep Neural Network; spoof detection; Neural Network; Mathematics and Statistics;

    Sammanfattning : Artificial neural networks are known to run into issues when given samples that deviate from the training distribution, where the network may confidently provide an incorrect answer. Out-of-distribution detection methods aims to provide a solution to this issue, by detecting data that deviates from the distribution used to train the model. LÄS MER

  5. 4. Improving Image Classification using Domain Adaptation for Autonomous Driving : A Master Thesis in Collaboration with Scania

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

    Författare :Mikael Westlund; [2023]
    Nyckelord :Autonomous driving; Deep Learning; Domain Adaptation; Image classification; LiDAR; Transfer Learning; Självkörande fordon; Djupinlärning; Domain Adaptation; Bildklassificering; LiDAR; Överföringsinlärning;

    Sammanfattning : Autonomous driving is a rapidly changing industry and has recently become a heavily focused research topic for vehicle producing companies and research organizations. These autonomous vehicles are typically equipped with sensors such as Light Detection and Radar (LiDAR) in order to perceive their surroundings. LÄS MER

  7. 5. Robust Graph SLAM in Challenging GNSS Environments Using Lidar Odometry

    Master-uppsats, Linköpings universitet/Reglerteknik

    Författare :Jesper Sundström; Alfred Åström; [2023]
    Nyckelord :graphslam; graph slam; graph; slam; automatic; control; robust; DCS; RRR; lidar odometry; gnss;

    Sammanfattning : Localization is a fundamental part of achieving fully autonomous vehicles. A localization system needs to constantly provide accurate information about the position of the vehicle and failure could lead to catastrophic consequences. LÄS MER