Sökning: "long short-term memory LSTM"
Visar resultat 1 - 5 av 263 uppsatser innehållade orden long short-term memory LSTM.
1. Audio Anomaly Detection in Cars
Master-uppsats, Göteborgs universitet/Institutionen för matematiska vetenskaperSammanfattning : Audio anomaly detection in the context of car driving is a crucial task for ensuring vehicle safety and identifying potential faults. This paper aims to investigate and compare different methods for unsupervised audio anomaly detection using a data set consisting of recorded audio data from fault injections and normal "no fault" driving. LÄS MER
2. Drivers of sea level variability using neural networks
Master-uppsats, Göteborgs universitet/Institutionen för geovetenskaperSammanfattning : Understanding the forcing of regional sea level variability is crucial as many people all over the world live along the coasts and are endangered by extreme sea levels and the global sea level rise. The adding of fresh water into the oceans due to melting of the Earth’s land ice together with thermosteric changes has led to a rise of the global mean sea level with an accelerating rate during the twentieth century. LÄS MER
3. 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
4. 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
5. Forecasting With Feature-Based Time Series Clustering
Master-uppsats, Jönköping University/Tekniska HögskolanSammanfattning : Time series prediction plays a pivotal role in various areas, including for example finance, weather forecasting, and traffic analysis. In this study, time series of historical sales data from a packaging manufacturer is used to investigate the effects that clustering such data has on forecasting performance. LÄS MER