Sökning: "Road scenes"

Visar resultat 1 - 5 av 12 uppsatser innehållade orden Road scenes.

  1. 1. Assessing the Efficiency of COLMAP, DROID-SLAM, and NeRF-SLAM in 3D Road Scene Reconstruction

    Master-uppsats, Lunds universitet/Matematik LTH

    Författare :Marcus Ascard; Farjam Movahedi; [2023]
    Nyckelord :3D reconstruction; Visual SLAM; Pose evaluation; Point cloud evaluation; Road scenes; Technology and Engineering;

    Sammanfattning : 3D reconstruction is a field in computer vision which has evolved rapidly as a result of the recent advancements in deep learning. As 3D reconstruction pipelines now can run in real-time, this has opened up new possibilities for teams developing Advanced Driver Assistance Systems (ADAS), which rely on the camera system of the vehicle to enhance the safety and driving experience. LÄS MER

  3. 2. Off-road Driving with Deteriorated Road Conditions for Autonomous Driving Systems

    Master-uppsats, Linköpings universitet/Institutionen för systemteknik

    Författare :Eric Ekström; [2022]
    Nyckelord :autonomous driving systems; computer graphics; synthetic training data; driving;

    Sammanfattning : Recent studies on robustness of machine learning systems shows that today’s autonomous vehicles struggle with very basic visual disturbances such as rain or snow. There is also a lack of training data that includes off road scenes or scenes with different forms of deformation to the road surface. LÄS MER

  4. 3. Transformer Based Object Detection and Semantic Segmentation for Autonomous Driving

    Master-uppsats, Linköpings universitet/Datorseende

    Författare :Mikaela Hardebro; Elin Jirskog; [2022]
    Nyckelord :Computer Vision; Autonomous Driving; Machine Learning; Transformers; Swin; CNN; Object Detection; Semantic Segmentation; Grad-CAM; PCA; Mean Attention Distance;

    Sammanfattning : The development of autonomous driving systems has been one of the most popular research areas in the 21st century. One key component of these kinds of systems is the ability to perceive and comprehend the physical world. Two techniques that address this are object detection and semantic segmentation. LÄS MER

  5. 4. Self-Supervised Representation Learning for Content Based Image Retrieval

    Master-uppsats, Linköpings universitet/Statistik och maskininlärning

    Författare :Hariprasath Govindarajan; [2020]
    Nyckelord :Content Based Image Retrieval; CBIR; Representation Learning; Self Supervised Learning; Unsupervised Learning; Attention Mechanism; Noise Contrastive Estimation; Autonomous Driving;

    Sammanfattning : Automotive technologies and fully autonomous driving have seen a tremendous growth in recent times and have benefitted from extensive deep learning research. State-of-the-art deep learning methods are largely supervised and require labelled data for training. LÄS MER

  7. 5. Active Learning for Road Segmentation using Convolutional Neural Networks

    Master-uppsats, Linköpings universitet/Datorseende

    Författare :Michael Sörsäter; [2018]
    Nyckelord :Active learning; Monte Carlo dropout; Semantic Segmentation; Convolutional Neural Networks; Uncertainty; CNN; Deep Learning; Road Segmentation; Machine learning;

    Sammanfattning : In recent years, development of Convolutional Neural Networks has enabled high performing semantic segmentation models. Generally, these deep learning based segmentation methods require a large amount of annotated data. Acquiring such annotated data for semantic segmentation is a tedious and expensive task. LÄS MER