Sökning: "Dator- seende"

Hittade 3 uppsatser innehållade orden Dator- seende.

  1. 1. Smart Scooter : Solving e-scooter safety problems with multi-modal, privacy-preserving sensor technology and machine learning

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

    Författare :Beatrice Lovely; [2022]
    Nyckelord :Smart Devices; Machine Learning; Sensors; Radar; Inertial Measurement Unit; Computer Vision; Smarta Saker; Maskininlärning; Sensorer; Radar; Tröghetsmåttenhet; Dator- seende;

    Sammanfattning : Micromobility ride-share scooters (e-scooters) have become a popular mode of transport in several major cities around the world, yet several safety and accessibility issues stem from how these scooters are operated, including sidewalk riding, unsafe parking and wrong-way riding. This thesis tackles these issues through a novel, privacy-preserving, end-to-end sensor system that employs lightweight machine learning models to provide real-time feedback to users to present unsafe scooter operation. LÄS MER

  2. 2. Receipt Scanning Using Deep Learning

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

    Författare :Gustaf Gunér; [2020]
    Nyckelord :;

    Sammanfattning : Employees often make purchases on behalf of the companies that they are working for. These purchases must be reported manually, either by the employees themselves or by sending the receipts to the company‘s accountant. In both cases, parts of the receipts are transcribed manually. LÄS MER

  3. 3. Recognizing Semantics in Human Actions with Object Detection

    Master-uppsats, KTH/Skolan för datavetenskap och kommunikation (CSC)

    Författare :Oscar Friberg; [2017]
    Nyckelord :Convolutional; Neural Networks; Artificial; Computer; Vision; Human; Action; Recognition; Faltnings; Neurala nätverk; Artificiell; Dator; Seende; Mänsklig; Aktivitet; Igänkänning;

    Sammanfattning : Two-stream convolutional neural networks are currently one of the most successful approaches for human action recognition. The two-stream convolutional networks separates spatial and temporal information into a spatial stream and a temporal stream. LÄS MER