Sökning: "ensemble learning"
Visar resultat 11 - 15 av 218 uppsatser innehållade orden ensemble learning.
11. Predicting Breakdowns in Transportation Vehicles using Supervised Learning
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Vehicle breakdowns can lead to fatal accidents, increase costs and reduce productivity. Therefore, robust and accurate fault diagnosis and prediction systems are critical to ensure the proper operation of vehicles. Many researchers have used machine learning for the prediction of vehicle breakdowns. LÄS MER
12. Rogue Drone Detection
Master-uppsats, Luleå tekniska universitet/Institutionen för system- och rymdteknikSammanfattning : Rogue drones have become a significant concern in recent years due to their potential to cause harm to people and property and disrupt critical infrastructure and public safety. As a result, there has been a growing need for effective methods to detect and mitigate the risks posed by these drones. LÄS MER
13. Data Augmentations for Improving Vision-Based Damage Detection : in Land Transport Infrastructure
Master-uppsats, KTH/Lantmäteri – fastighetsvetenskap och geodesiSammanfattning : Crack, a typical term most people know, is a common form of distress or damage in road pavements and railway sleepers. It poses significant challenges to their structural integrity, safety, and longevity. Over the years, researchers have developed various data-driven technologies for image-based crack detection in road and sleeper applications. LÄS MER
14. Improving Visibility Forecasts in Denmark Using Machine Learning Post-processing
Master-uppsats, Uppsala universitet/Luft-, vatten- och landskapsläraSammanfattning : Accurate fog prediction is an important task facing forecast centers since low visibility can affect anthropogenic systems, such as aviation. Therefore, this study investigates the use of Machine Learning classification algorithms for post-processing the output of the Danish Meteorological Institute’s operational Numerical Weather Prediction (NWP) model to improve visibility prediction. LÄS MER
15. Generation of a metrical grid informed by Deep Learning-based beat estimation in jazz-ensemble recordings
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : This work uses a Deep Learning architecture, specifically a state-of-the-art Temporal Convolutional Network, to track the beat and downbeat positions in jazz-ensemble recordings to derive their metrical grid. This network architecture has been used successfully for general beat tracking purposes. LÄS MER