Sökning: "Object detector"

Visar resultat 1 - 5 av 125 uppsatser innehållade orden Object detector.

  1. 1. Data Augmentation for Object Detection using Deep Reinforcement Learning

    Uppsats för yrkesexamina på avancerad nivå, Lunds universitet/Institutionen för reglerteknik

    Författare :Axel Andersson; Nils Hallerfelt; [2024]
    Nyckelord :Technology and Engineering;

    Sammanfattning : Data augmentation is a concept which is used to improve machine learning models for computer vision tasks. It is usually done by firstly, defining a set of functions which transforms images and secondly, applying a random selection of these functions on the images. LÄS MER

  3. 2. Evaluation of FMCW Radar Jamming Sensitivity

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Signaler och system

    Författare :Ludvig Snihs; [2023]
    Nyckelord :FMCW; FMCW radar; radar; frequency-modulated radar; noise jamming; frequency-modulated continuous wave radar; FMCW Jamming; Jamming; Pulse Train; Pulse Jamming; Spoofing Attack; Spoofing; Deception; Repeater Jamming; Repeater; Automotive Radar; CFAR; sensor jamming; constant false alarm rate; electronic warfare; EW; FMCW; FMCW radar; frekvensmodulerad dopplerradar; dopplerradar; radar; brusstörning; radarstörning; pulsstörning; pulståg; falskmål; vilseledning; repeterstörning; bilradar; sensorstörning; CFAR;

    Sammanfattning : In this work, the interference sensitivity of an FMCW radar has been evaluated by studying the impact on a simulated detection chain. A commercially available FMCW radar was first characterized and its properties then laid the foundation for a simulation model implemented in Matlab. LÄS MER

  4. 3. Autonomous Navigation in Partially-Known Environment using Nano Drones with AI-based Obstacle Avoidance : A Vision-based Reactive Planning Approach for Autonomous Navigation of Nano Drones

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

    Författare :Mattia Sartori; [2023]
    Nyckelord :Nano Drones; Obstacle Avoidance; Autonomous Exploration; Autonomous Surveillance; Resource-Constrained Drones; Safe Navigation; Reactive Planning; Vision-based Navigation; Nanodrönare; Undvikande av Hinder; Autonom Utforskning; Autonom Övervakning; Resursbegränsade Drönare; Säker Navigering; Reaktiv Planering; Visionsbaserad Navigering;

    Sammanfattning : The adoption of small-size Unmanned Aerial Vehicles (UAVs) in the commercial and professional sectors is rapidly growing. The miniaturisation of sensors and processors, the advancements in connected edge intelligence and the exponential interest in Artificial Intelligence (AI) are boosting the affirmation of autonomous nano-size drones in the Internet of Things (IoT) ecosystem. LÄS MER

  5. 4. KARTAL: Web Application Vulnerability Hunting Using Large Language Models : Novel method for detecting logical vulnerabilities in web applications with finetuned Large Language Models

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

    Författare :Sinan Sakaoglu; [2023]
    Nyckelord :Broken Access Control; Vulnerability; Large Language Models; Web Application; API; Detection; Scanner; DAST; Application Security; Brutet åtkomstkontroll; Sårbarhet; Stora språkmodeller; Webbapplikation; API; Upptäckt; Skanner; DAST; Applikationssäkerhet;

    Sammanfattning : Broken Access Control is the most serious web application security risk as published by Open Worldwide Application Security Project (OWASP). This category has highly complex vulnerabilities such as Broken Object Level Authorization (BOLA) and Exposure of Sensitive Information. LÄS MER

  7. 5. Semi-Supervised Head Detection for Low Resolution Images

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

    Författare :Annie Biby Rapheal; [2023]
    Nyckelord :Object detection; Semi Supervised Learning; Head detection; Objektdetektion; Semisupervised Learning; Huvuddetektion;

    Sammanfattning : Object detection is a widely researched and applied field in computer vision. Deep learning models have successfully been used for object detection over the years. The performance of State of the art (SOTA) object detection deep learning models is dependent on the number of labeled images. LÄS MER