Sökning: "Intersection Detection"

Visar resultat 1 - 5 av 43 uppsatser innehållade orden Intersection Detection.

  1. 1. Leveraging CNN for Automated Peak Picking in Untargeted Metabolomics without Parameter Dependencies

    Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

    Författare :Vivian Wang; Lidia Yalew; [2023-10-19]
    Nyckelord :Deep learning; Convolutional neural network; LC-MS; Peak Detection; Metabolomics; Faster R-CNN;

    Sammanfattning : Metabolomics is a scientific discipline that involves the thorough analysis of small molecules, known as metabolites, found within a biological system. Furthermore, liquid chromatography-mass spectrometry (LC-MS) is a commonly used analytical technique in metabolomics for analysing biological samples due to its broad coverage of the measurable metabolome. LÄS MER

  3. 2. Deep Learning Model Deployment for Spaceborne Reconfigurable Hardware : A flexible acceleration approach

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

    Författare :Javier Ferre Martin; [2023]
    Nyckelord :Space Situational Awareness; Deep Learning; Convolutional Neural Networks; FieldProgrammable Gate Arrays; System-On-Chip; Computer Vision; Dynamic Partial Reconfiguration; High-Level Synthesis; Rymdsituationstänksamhet; Djupinlärning; Konvolutionsnätverk; Omkonfigurerbara Field-Programmable Gate Arrays FPGAs ; System-On-Chip SoC ; Datorseende; Dynamisk partiell omkonfigurering; Högnivåsyntes.;

    Sammanfattning : Space debris and space situational awareness (SSA) have become growing concerns for national security and the sustainability of space operations, where timely detection and tracking of space objects is critical in preventing collision events. Traditional computer-vision algorithms have been used extensively to solve detection and tracking problems in flight, but recently deep learning approaches have seen widespread adoption in non-space related applications for their high accuracy. LÄS MER

  4. 3. Exploration of Radar Cross Section Models and Distributed Sensing Techniques in JCAS Cell-free Massive MIMO

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

    Författare :Qinglin Zou; [2023]
    Nyckelord :Joint communication and sensing; Cell-free massive MIMO; Swerling models; Distributed Sensing; Gemensam kommunikation och avkänning; Cellfri massiv MIMO; Swerling modeller; Distributed Sensing;

    Sammanfattning : Joint Communication and Sensing (JCAS) technology enables the sharing of infrastructure, resources, and signals between communication and sensing. However, studying the performance and algorithms using appropriate target reflectivity models for detection poses a significant challenge. LÄS MER

  5. 4. Hybrid Deep Learning approach for Lane Detection : Combining convolutional and transformer networks with a post-processing temporal information mechanism, for efficient road lane detection on a road image scene

    Master-uppsats, Jönköping University/Jönköping AI Lab (JAIL)

    Författare :Dimitrios Zarogiannis; Stelio Bompai; [2023]
    Nyckelord :Lane Detection; CNN; Vision Transformer; Deep Learning; Semantic Segmentation; Computer Vision;

    Sammanfattning : Lane detection is a crucial task in the field of autonomous driving and advanced driver assistance systems. In recent years, convolutional neural networks (CNNs) have been the primary approach for solving this problem. LÄS MER

  7. 5. Reliable Detection of Water Areas in Multispectral Drone Imagery : A faster region-based CNN model for accurately identifying the location of small-scale standing water bodies

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

    Författare :Shengyao Shangguan; [2023]
    Nyckelord :Water Detection; Faster region-based convolutional neural networks; Multiple images; Convolutional neural networks; Random Forest; Vattendetektering; Snabbare regionbaserade konvolutionella neurala nätverk; Flera bilder; Konvolutionella neurala nätverk; Random Forest;

    Sammanfattning : Dengue and Zika are two arboviral viruses that affect a significant portion of the world population. The principal vector species of both viruses are Aedes aegypti and Aedes albopictus mosquitoes. They breed in very slow flowing or standing pools of water. LÄS MER