Sökning: "image localisation"
Visar resultat 1 - 5 av 21 uppsatser innehållade orden image localisation.
1. Modulating Depth Map Features to Estimate 3D Human Pose via Multi-Task Variational Autoencoders
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Human pose estimation (HPE) constitutes a fundamental problem within the domain of computer vision, finding applications in diverse fields like motion analysis and human-computer interaction. This paper introduces innovative methodologies aimed at enhancing the accuracy and robustness of 3D joint estimation. LÄS MER
2. Visual-Inertial SLAM Using a Monocular Camera and Detailed Map Data
Master-uppsats, Linköpings universitet/ReglerteknikSammanfattning : The most commonly used localisation methods, such as GPS, rely on external signals to generate an estimate of the location. There is a need of systems which are independent of external signals in order to increase the robustness of the localisation capabilities. LÄS MER
3. The role of AmotL2 in the regulation of mesenchymal transitioning of endothelial cells
Master-uppsats, Uppsala universitet/Institutionen för medicinsk biokemi och mikrobiologiSammanfattning : Background During development, endothelial cells acquire mesenchymal-like properties to migrate and facilitate normal vascular formation. This process of transformation is known as endothelial to mesenchymal transition (EndMT) and has also been implicated in diseases like vascular pathologies contributing to endothelial inflammation, atherosclerosis and tumour angiogenesis. LÄS MER
4. Effects of reconstruction parameters on the image quality and quantification of PET images from PET/MRI and PET/CT systems
Master-uppsats,Sammanfattning : Aim: To study how reconstruction parameters affect the positron emission tomography (PET) image quality and quantitative results for the different lesion to background radioactivity ratios in three different PET systems. Introduction: Multimodality imaging that combines magnetic resonance imaging (MRI) or computed tomography (CT) with a PET system can produce medical images containing both functional and anatomical information. LÄS MER
5. Deep neural networks for food waste analysis and classification : Subtraction-based methods for the case of data scarcity
Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Signaler och systemSammanfattning : Machine learning generally requires large amounts of data, however data is often limited. On the whole the amount of data needed grows with the complexity of the problem to be solved. Utilising transfer learning, data augmentation and problem reduction, acceptable performance can be achieved with limited data for a multitude of tasks. LÄS MER