Sökning: "upsampling"
Visar resultat 1 - 5 av 17 uppsatser innehållade ordet upsampling.
1. Generative adversarial network for point cloud upsampling
Uppsats för yrkesexamina på avancerad nivå, Luleå tekniska universitet/Institutionen för system- och rymdteknikSammanfattning : Point clouds are a widely used system for the collection and application of 3D data. But most timesthe data gathered is too scarce to reliably be used in any application. LÄS MER
2. Virtual H&E Staining Using PLS Microscopy and Neural Networks
Master-uppsats, Lunds universitet/Matematik LTHSammanfattning : Histopathological examination, crucial in diagnosing diseases such as cancer, traditionally relies on time- and resource-consuming, poorly standardized chemical staining for tissue visualization. This thesis presents a novel digital alternative using generative neural networks and a point light source (PLS) microscope to transform unstained skin tissue images into their stained counterparts. LÄS MER
3. Exploring State-of-the-Art Machine Learning Methods for Quantifying Exercise-induced Muscle Fatigue
Uppsats för yrkesexamina på avancerad nivå, Högskolan i Halmstad/Akademin för informationsteknologiSammanfattning : Muscle fatigue is a severe problem for elite athletes, and this is due to the long resting times, which can vary. Various mechanisms can cause muscle fatigue which signifies that the specific muscle has reached its maximum force and cannot continue the task. LÄS MER
4. Deep learning for temporal super-resolution of 4D Flow MRI
Master-uppsats, KTH/Matematik (Avd.)Sammanfattning : The accurate assessment of hemodynamics and its parameters play an important role when diagnosing cardiovascular diseases. In this context, 4D Flow Magnetic Resonance Imaging (4D Flow MRI) is a non-invasive measurement technique that facilitates hemodynamic parameter assessment as well as quantitative and qualitative analysis of three-directional flow over time. LÄS MER
5. Radar Detection Using Deep Learning
Master-uppsats, Lunds universitet/Matematik LTHSammanfattning : This thesis aims to reproduce and improve a paper about dynamic road user detection on 2D bird's-eye-view radar point cloud in the context of autonomous driving. We choose RadarScenes, a recent large public dataset, to train and test deep neural networks. LÄS MER