Sökning: "Classification Algorithms"
Visar resultat 1 - 5 av 504 uppsatser innehållade orden Classification Algorithms.
1. Exploration and Evaluation of RNN Models on Low-Resource Embedded Devices for Human Activity RecognitionMaster-uppsats, KTH/Mekatronik och inbyggda styrsystem
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
2. Song Popularity Prediction with Deep Learning : Investigating predictive power of low level audio featuresMagister-uppsats, Luleå tekniska universitet/Institutionen för system- och rymdteknik
Sammanfattning : Today streaming services are the most popular way to consume music, and with this the field of Music Information Retrieval (MIR) has exploded. Tangy market is a music investment platform and they want to use MIR techniques to estimate the value of not yet released songs. LÄS MER
3. Optimization of Speed vs. Accuracy Trade-off in State-of-the-Art Object Detectors for Traffic Light DetectionMaster-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)
Sammanfattning : Traffic lights detection systems are an important area of research, aimed towards improving the accuracy and response time of self-driving vehicles when faced with traffic signals. This project attempted to find a solution for the speed-accuracy trade-off faced by traffic light detection systems. LÄS MER
4. Automatic event detection oncontinuous glucose datausing neural networksMaster-uppsats, KTH/Skolan för kemi, bioteknologi och hälsa (CBH)
Sammanfattning : Automatically detecting events for people with diabetes mellitus using continuousglucose monitors is an important step in allowing insulin pumps to automaticallycorrect the blood glucose levels and for a more hands-off approach to thedisease. The automatic detection of events could also aid physicians whenassisting their patients when referring to their continuous glucose monitordata. LÄS MER
5. Identification of Fibers in Micro-CT Images of Paperboard Using Deep LearningUppsats för yrkesexamina på avancerad nivå, Lunds universitet/Hållfasthetslära; Lunds universitet/Institutionen för byggvetenskaper
Sammanfattning : This master thesis project explores the possibility of using deep learning to segment individual fibers in three-dimensional tomography images of paperboard fiber networks. We test a method which has previously been used to segment fibers in images of glass fiber reinforced polymers. LÄS MER