Sökning: "Convolutions Neural Network CNN"
Visar resultat 1 - 5 av 7 uppsatser innehållade orden Convolutions Neural Network CNN.
1. Classification of ultrasonic signals using machine learning to identify optimal frequency for elongation control : Threaded fastening tools
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Studying the preload in a screw joint has been the focus of today’s industry. The manufacturer reflects that demand by investigating different opportunities and techniques to develop this area. There are four different ways of controlling the tightening of bolts and joints to achieve the required clamp force that can hold for a specific preload. LÄS MER
2. Convolutions on graphs for learning vehicle crash behaviour
Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknikSammanfattning : Convolutional Neural Networks (CNN) have shown successful results in the recent years, especially within the area of image analysis. The idea of learning to predict the result of a crash simulation using machine learning rose from the analogy between images and Finite Element models (FE-models) used in crash simulations. LÄS MER
3. GVT-BDNet : Convolutional Neural Network with Global Voxel Transformer Operators for Building Damage Assessment
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Natural disasters strike anywhere, disrupting local communication and transportation infrastructure, making the process of assessing specific local damage difficult, dangerous, and slow. The goal of Building Damage Assessment (BDA) is to quickly and accurately estimate the location, cause, and severity of the damage to maximize the efficiency of rescuers and saved lives. LÄS MER
4. Deep Learning for Earth Observation: improvement of classification methods for land cover mapping : Semantic segmentation of satellite image time series
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Satellite Image Time Series (SITS) are becoming available at high spatial, spectral and temporal resolutions across the globe by the latest remote sensing sensors. These series of images can be highly valuable when exploited by classification systems to produce frequently updated and accurate land cover maps. LÄS MER
5. Impact of using different brain layer amounts on the accuracy of Convolutional Neural networks trained on MR-Images to identify Parkinson's Disease
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Parkinson’s Disease (PD) is a neurodegenerative disease and brain disorder which affects the motor system and leads to shaking, stiffness, impaired balance and coordination. Diagnosing PD from Magnetic resonance images (MR-images) is difficult and often not possible for medical experts and therefore Convolutional neural networks (CNNs) are used instead. LÄS MER
