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Visar resultat 1 - 5 av 24 uppsatser som matchar ovanstående sökkriterier.

  1. 1. Optimization of Speed vs. Accuracy Trade-off in State-of-the-Art Object Detectors for Traffic Light Detection

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

    Författare :Vikash Lal Dodani; [2023]
    Nyckelord :Machine Learning; Computer Vision; Traffic Lights Detection; Self-Driving Cars; BOSCH; BSTLD; LISA;

    Sammanfattning : Traffic lights detection systems are an important area of research, aimed towards improving the accuracy and response time of self-driving vehicles when faced with traffic signals. This project attempted to find a solution for the speed-accuracy trade-off faced by traffic light detection systems. LÄS MER

  3. 2. 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

  4. 3. A Comparison of Convolutional Neural Networks used in Melanoma Detection : With transfer learning on the PAD-UFES-20 and ISIC datasets

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

    Författare :Abdi Gobena; [2023]
    Nyckelord :Machine learning; Neural networks; Skin cancer; PAD-UFES-20; ISIC; Maskininlärning; Neuronnätverk; Hudcancer; PAD-UFES-20; ISIC;

    Sammanfattning : Skin cancer is one of the most common forms of cancer, of which melanoma is the most lethal. Early detection is critical to long term survival rates. The use of machine learning to detect melanoma shows promising results in detecting malignant forms. LÄS MER

  5. 4. Objektdetektering av trafikskyltar på inbyggda system med djupinlärning

    Kandidat-uppsats, Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)

    Författare :Pontus Wikström; Johan Hotakainen; [2023]
    Nyckelord :Deep learning; Edge device; Machine learning; Nvidia Jetson Nano; Objectdetection; Raspberry Pi 3; Traffic sign recognition; Djupinlärning; Inbyggda system; Maskininlärning; Nvidia Jetson Nano; Objektdetektering; Raspberry Pi 3; Trafikskyltsigenkänning;

    Sammanfattning : In recent years, AI has developed significantly and become more popular than ever before. The applications of AI are expanding, making knowledge about its application and the systems it can be applied to more important. LÄS MER

  7. 5. Automatic Man Overboard Detection with an RGB Camera : Using convolutional neural networks

    Master-uppsats, Linköpings universitet/Artificiell intelligens och integrerade datorsystem

    Författare :William Bergekrans; [2022]
    Nyckelord :man overboard; object detection; computer vision; man overboard dataset;

    Sammanfattning : Man overboard is one of the most common and dangerous accidents that can occur whentraveling on a boat. Available research on man overboard systems with cameras have focusedon man overboard taking place from larger ships, which involves a fall from a height. LÄS MER