Sökning: "Temporal Convolutional Network"
Visar resultat 1 - 5 av 62 uppsatser innehållade orden Temporal Convolutional Network.
1. Time Series Forecasting on Database Storage
Kandidat-uppsats, Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)Sammanfattning : Time Series Forecasting has become vital in various industries ranging from weather forecasting to business forecasting. There is a need to research database storage solutions for companies in order to optimize resource allocation, enhance decision making process and enable predictive data storage maintenance. LÄS MER
2. Heart rate estimation from wrist-PPG signals in activity by deep learning methods
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)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. Neural Network-based Anomaly Detection Models and Interpretability Methods for Multivariate Time Series Data
Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskapSammanfattning : Anomaly detection plays a crucial role in various domains, such as transportation, cybersecurity, and industrial monitoring, where the timely identification of unusual patterns or outliers is of utmost importance. Traditional statistical techniques have limitations in handling complex and highdimensional data, which motivates the use of deep learning approaches. LÄS MER
4. Anomaly Detection in the EtherCAT Network of a Power Station : Improving a Graph Convolutional Neural Network Framework
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : In this thesis, an anomaly detection framework is assessed and fine-tuned to detect and explain anomalies in a power station, where EtherCAT, an Industrial Control System, is employed for monitoring. The chosen framework is based on a previously published Graph Neural Network (GNN) model, utilizing attention mechanisms to capture complex relationships between diverse measurements within the EtherCAT system. LÄS MER
5. Finding the QRS Complex in a Sampled ECG Signal Using AI Methods
Master-uppsats, KTH/FysikSammanfattning : This study aimed to explore the application of artificial intelligence (AI) and machine learning (ML) techniques in implementing a QRS detector forambulatory electrocardiography (ECG) monitoring devices. Three ML models, namely long short-term memory (LSTM), convolutional neural network (CNN), and multilayer perceptron (MLP), were compared and evaluated using the MIT-BIH arrhythmia database (MITDB) and the MIT-BIH noise stress test database (NSTDB). LÄS MER