Sökning: "real-world network data"

Visar resultat 21 - 25 av 186 uppsatser innehållade orden real-world network data.

  1. 21. The influence of neural network-based image enhancements on object detection

    Kandidat-uppsats, Högskolan i Skövde/Institutionen för informationsteknologi

    Författare :Eric Pettersson; Muhammed Al Khayyat; [2023]
    Nyckelord :Object detection; YOLO; image enhancement; ESRGAN; Zero-DCE;

    Sammanfattning : This thesis investigates the impact of image enhancement techniques on object detection for carsin real-world traffic scenarios. The study focuses on upscaling and light correction treatments andtheir effects on detecting cars in challenging conditions. Initially, a YOLOv8x model is trained on clear static car images. LÄS MER

  3. 22. Fault Detection and Diagnosis for Automotive Camera using Unsupervised Learning

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

    Författare :Ziyou Li; [2023]
    Nyckelord :Unsupervised Learning; Autoencoders; Image Clustering; Fault Detection and Diagnosis; Morphological Operations; Hardware-in-Loop; Advanced DriverAssistance System; Oövervakad inlärning; Autoencoders; Bildklustering; Felfindning och Diagnostik; Morfologiska Operationer; Hardware-in-Loop; Avancerade Förarassistanssystem;

    Sammanfattning : This thesis aims to investigate a fault detection and diagnosis system for automotive cameras using unsupervised learning. 1) Can a front-looking wide-angle camera image dataset be created using Hardware-in-Loop (HIL) simulations? 2) Can an Adversarial Autoencoder (AAE) based unsupervised camera fault detection and diagnosis method be crafted for SPA2 Vehicle Control Unit (VCU) using an image dataset created using Hardware-inLoop? 3) Does using AAE surpass the performance of using Variational Autoencoder (VAE) for the unsupervised automotive camera fault diagnosis model? In the field of camera fault studies, automotive cameras stand out for its complex operational context, particularly in Advanced Driver-Assistance Systems (ADAS) applications. LÄS MER

  4. 23. Exploring Game Balance and Tactics with AI in the Educational Wargame Counter-Air

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

    Författare :Lucas Pelz; Melker Bengtsson; [2023]
    Nyckelord :;

    Sammanfattning : This report describes a study of the game balance of the wargame Counter-Air,using the artificial intelligence model AlphaZero. The project also analyzed the most effectivestrategies in the game regarding allocation of pieces to a set number of roles. Counter-Air is a board game being developed for use in tactical training of military officers. LÄS MER

  5. 24. Evaluation of Ferroelectric Tunnel Junction memristor for in-memory computation in real world use cases

    Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknik

    Författare :Alec Guerin; Christos Papadopoulos; [2023]
    Nyckelord :FTJ; Ferroelectric Tunneling Junction; Analog in-memory computing; AIMC; Memristor; A.I.; AIHWKIT; Semantic segmentation; Natural Language Processing; NLP; Neuromorphic Computing; Matrix Vector Multiplication; Technology and Engineering;

    Sammanfattning : Machine learning algorithms are experiencing unprecedented attention, but their inherent computational complexity leads to high energy consumption. However, a paradigm shift in computing methods has the potential to address the issue. LÄS MER

  7. 25. Processing world scale air traffic data to find Near Mid-Air Collisions

    Kandidat-uppsats, KTH/Skolan för teknikvetenskap (SCI)

    Författare :Leopold Hermansson; [2023]
    Nyckelord :Air traffic safety; Detect and Avoid; ADS-B;

    Sammanfattning : In order to increase the safety of all air travel, technologies that continueto augment the pilot's ability to avoid collisions and stay clear of danger areneeded. But, before these can be certified and deployed, their performance andpotential failure cases have to be understood. LÄS MER