Sökning: "Long Short-Term Memory LSTM"
Visar resultat 1 - 5 av 153 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. Förutsäga spelresultat i Dota 2 med NLP och maskininlärningsalgoritmer
Master-uppsats, Jönköping University/JTH, Avdelningen för datateknik och informatikSammanfattning : Esports has grown quickly in recent years, and the business has produced a ton of specifications-based data that is simple to obtain. Because of the aforementioned traits, data mining and deep learning techniques can be used to direct participants and create winning strategies. LÄS MER
4. Predicting Cryptocurrency Prices with Machine Learning Algorithms: A Comparative Analysis
Kandidat-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskapSammanfattning : Background: Due to its decentralized nature and opportunity for substantial gains, cryptocurrency has become a popular investment opportunity. However, the highly unpredictable and volatile nature of the cryptocurrency market poses a challenge for investors looking to predict price movements and make profitable investments. LÄS MER
5. Exploration and Evaluation of RNN Models on Low-Resource Embedded Devices for Human Activity Recognition
Master-uppsats, KTH/Mekatronik och inbyggda styrsystemSammanfattning : 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