Sökning: "Multiple Object Detection"

Visar resultat 1 - 5 av 72 uppsatser innehållade orden Multiple Object Detection.

  1. 1. Automatic Semantic Segmentation of Indoor Datasets

    Master-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

    Författare :Sai Swaroop Rachakonda; [2024]
    Nyckelord :Semantic Segmentation; Annotation; SLAM; Indoor datasets; YOLO V8; DETIC; Segment Anything Model.;

    Sammanfattning : Background: In recent years, computer vision has undergone significant advancements, revolutionizing fields such as robotics, augmented reality, and autonomoussystems. Key to this transformation is Simultaneous Localization and Mapping(SLAM), a fundamental technology that allows machines to navigate and interactintelligently with their surroundings. LÄS MER

  3. 2. Dasty : Revealing Real-World Prototype Pollution Consequences with Dynamic Taint Analysis

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

    Författare :Paul Moosbrugger; [2023]
    Nyckelord :Prototype Pollution Gadgets; Dynamic Taint Analysis; Forced Branch Execution; NodeProf Instrumentation; Truffle GraalJS;

    Sammanfattning : Prototype pollution is a vulnerability in JavaScript and other prototype-based languages that allows malicious actors to inject a property into an object’s prototype. The injected property can subsequently trigger gadgets - source code sections that use the properties in sensitive locations. LÄS MER

  4. 3. Object Recognition and Tracking of Bolts: A Comparative Analysis of CNN Models and Computer Vision Techniques : A Comparison of CNN Models and Tracking Algorithms

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

    Författare :Serhat Bulun; [2023]
    Nyckelord :;

    Sammanfattning : The newer generation industry 4.0 focuses on development of both flexibility and autonomy for power tools used by companies in different mechanical areas and assembly lines. One area for automation is the application of computer vision in power tools to detect, identify and track bolts. LÄS MER

  5. 4. Using Machine Learning to Optimize Near-Earth Object Sighting Data at the Golden Ears Observatory

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

    Författare :Laura Murphy; [2023]
    Nyckelord :Near-Earth Object Detection; Machine Learning; Deep Learning; Visual Transformers;

    Sammanfattning : This research project focuses on improving Near-Earth Object (NEO) detection using advanced machine learning techniques, particularly Vision Transformers (ViTs). The study addresses challenges such as noise, limited data, and class imbalance. LÄS MER

  7. 5. Smart Tracking for Edge-assisted Object Detection : Deep Reinforcement Learning for Multi-objective Optimization of Tracking-based Detection Process

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

    Författare :Shihang Zhou; [2023]
    Nyckelord :Tracking-By-Detection; Deep Reinforcement Learning; Multi-Objective Optimization; Spårning genom detektion; Djup förstärkningsinlärning; Multiobjektiv optimering;

    Sammanfattning : Detecting generic objects is one important sensing task for applications that need to understand the environment, for example eXtended Reality (XR), drone navigation etc. However, Object Detection algorithms are particularly computationally heavy for real-time video analysis on resource-constrained mobile devices. LÄS MER