Sökning: "point cloud segmentation"

Visar resultat 11 - 15 av 34 uppsatser innehållade orden point cloud segmentation.

  1. 11. LiDAR Point Cloud De-noising for Adverse Weather

    Master-uppsats, Högskolan i Halmstad/Akademin för informationsteknologi

    Författare :Johan Bergius; Jesper Holmblad; [2022]
    Nyckelord :Semantic Segmentation; Lidar point cloud; CNN; GAN; CycleGAN; Unsupervised; LiOR; DSOR; DROR; WADS;

    Sammanfattning : Light Detection And Ranging (LiDAR) is a hot topic today primarily because of its vast importance within autonomous vehicles. LiDAR sensors are capable of capturing and identifying objects in the 3D environment. However, a drawback of LiDAR is that they perform poorly under adverse weather conditions. LÄS MER

  3. 12. Segmentation, Classification and Tracking of Objects in LiDAR Point Cloud Data Using Deep Learning

    Master-uppsats, Lunds universitet/Matematik LTH

    Författare :Hjalmar Lind; Robin Holtz Bernståle; [2022]
    Nyckelord :Deep Learning; Point Cloud; Segmentation; Classification; Tracking; LiDAR; PointNet; Technology and Engineering;

    Sammanfattning : The purpose of this thesis was to explore deep learning methods of segmentation, classification and tracking of objects in LiDAR data. To do this a complete pipeline was developed, consisting of background filtering, clustering, tracking, labeling and visualization. LÄS MER

  4. 13. Improving a Background Model for Tracking and Classification of Objects in LiDAR 3D Point Clouds

    Master-uppsats, Lunds universitet/Matematik LTH

    Författare :Seamus Doyle; Gustav Nilsson; [2022]
    Nyckelord :LiDAR; Semantic Segmentation; Neural Networks; RandLA-NET; 3D Point Cloud; Gaussian Process Regression; Robust Locally Weighted Regression; CARLA; Ground Model; Technology and Engineering;

    Sammanfattning : This thesis studied methods of improving a background model for a data processing pipeline of LiDAR point clouds. For this, two main approaches were evaluated. The first was to implement and compare three different models for detecting ground in a point cloud. These were based on more classical modeling approaches. LÄS MER

  5. 14. Radar Detection Using Deep Learning

    Master-uppsats, Lunds universitet/Matematik LTH

    Författare :Ziliang Xiong; Leonardo Carrera; [2022]
    Nyckelord :Deep Learning; Autonomous Driving; Radar; Point Cloud; Technology and Engineering;

    Sammanfattning : This thesis aims to reproduce and improve a paper about dynamic road user detection on 2D bird's-eye-view radar point cloud in the context of autonomous driving. We choose RadarScenes, a recent large public dataset, to train and test deep neural networks. LÄS MER

  7. 15. Deep Learning Semantic Segmentation of 3D Point Cloud Data from a Photon Counting LiDAR

    Master-uppsats, Linköpings universitet/Datorseende

    Författare :Caspian Süsskind; [2022]
    Nyckelord :Deep Learning; Machine Learning; Computer vision; Semantic Segmentation; Photon Counting LiDAR; LiDAR; Point Cloud; 3D Data; Point Cloud Segmentation; Point Classification; Convolutional Neural Network; CNN; SPVCNN; Djupinlärning; LiDAR; fotonräknande LiDAR; semantisk segmentering; datorseende; punktmoln; maskininlärning;

    Sammanfattning : Deep learning has shown to be successful on the task of semantic segmentation of three-dimensional (3D) point clouds, which has many interesting use cases in areas such as autonomous driving and defense applications. A common type of sensor used for collecting 3D point cloud data is Light Detection and Ranging (LiDAR) sensors. LÄS MER