Sökning: "Embedded Machine Learning"

Visar resultat 1 - 5 av 81 uppsatser innehållade orden Embedded Machine Learning.

  1. 1. Heart rate estimation from wrist-PPG signals in activity by deep learning methods

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

    Författare :Marie-Ange Stefanos; [2023]
    Nyckelord :Deep Learning; Medical Data; Signal Processing; Heart Rate Estimation; Wrist Photoplethysmography; Djup lärning; Medicinska Data; Signalbehandling; Pulsuppskattning; Handledsfotopletysmograf;

    Sammanfattning : In the context of health improving, the measurement of vital parameters such as heart rate (HR) can provide solutions for health monitoring, prevention and screening for certain chronic diseases. Among the different technologies for HR measuring, photoplethysmography (PPG) technique embedded in smart watches is the most commonly used in the field of consumer electronics since it is comfortable and does not require any user intervention. LÄS MER

  3. 2. DISTRIBUTED ARTIFICIAL INTELLIGENCE FOR ANOMALY DETECTION IN A MODULAR MANUFACTURING ENVIRONMENT

    Magister-uppsats, Mälardalens universitet/Akademin för innovation, design och teknik

    Författare :Hana Hodzic; [2023]
    Nyckelord :;

    Sammanfattning : This thesis investigates anomaly detection and classification in a simulated modular manufacturingenvironment using Machine Learning algorithm Random Forest. This algorithm is tested on a localcomputer and an embedded device, specifically the Raspberry PI. LÄS MER

  4. 3. Exploration and Evaluation of RNN Models on Low-Resource Embedded Devices for Human Activity Recognition

    Master-uppsats, KTH/Mekatronik och inbyggda styrsystem

    Författare :Helgi Hrafn Björnsson; Jón Kaldal; [2023]
    Nyckelord :Recurrent Neural Networks; Long Short-Term Memory Networks; Embedded Systems; Human Activity Recognition; Edge AI; TensorFlow Lite Micro; Recurrent Neural Networks; Long Short-Term Memory Networks; Innbyggda systyem; Mänsklig aktivitetsigenkänning; Edge AI; TensorFlow Lite Micro;

    Sammanfattning : Human activity data is typically represented as time series data, and RNNs, often with LSTM cells, are commonly used for recognition in this field. However, RNNs and LSTM-RNNs are often too resource-intensive for real-time applications on resource constrained devices, making them unsuitable. LÄS MER

  5. 4. Anomaly Detection for Network Traffic in a Resource Constrained Environment

    Master-uppsats, Mälardalens universitet/Akademin för innovation, design och teknik

    Författare :Pontus Lidholm; Gaia Ingletto; [2023]
    Nyckelord :Network Traffic; Anomaly Detection; Embedded Systems; Machine Learning; Random Forest;

    Sammanfattning : Networks connected to the internet are under a constant threat of attacks. To protect against such threats, new techniques utilising already connected hardware have in this thesis been proven to be a viable solution. LÄS MER

  7. 5. Classification of Cable Shoe Presses on an Embedded System Using a Neural Network Implemented by Hand

    Master-uppsats, Umeå universitet/Institutionen för datavetenskap

    Författare :Charlotta Nordlund; [2023]
    Nyckelord :;

    Sammanfattning : Pressing cables with cable shoes currently involves the use of high pressure to ensure successful crimping. However, this approach lacks the ability to detect when the pressing has been completed. Elpress intends to develop a handheld tool that can classify cables in real-time and stop the pressing before unnecessary energy is lost. LÄS MER