Sökning: "Image Segmentation"
Visar resultat 1 - 5 av 431 uppsatser innehållade orden Image Segmentation.
1. Automatic Semantic Segmentation of Indoor Datasets
Master-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskapSammanfattning : Background: In recent years, computer vision has undergone significant advancements, revolutionizing fields such as robotics, augmented reality, and autonomoussystems. Key to this transformation is Simultaneous Localization and Mapping(SLAM), a fundamental technology that allows machines to navigate and interactintelligently with their surroundings. LÄS MER
2. Mutual Enhancement of Environment Recognition and Semantic Segmentation in Indoor Environment
Master-uppsats,Sammanfattning : Background:The dynamic field of computer vision and artificial intelligence has continually evolved, pushing the boundaries in areas like semantic segmentation andenvironmental recognition, pivotal for indoor scene analysis. This research investigates the integration of these two technologies, examining their synergy and implicayions for enhancing indoor scene understanding. LÄS MER
3. Despeckling Echocardiograms Using Generative Adversarial Networks
Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknikSammanfattning : Previous research had shown that generative adversarial networks (GANs) are capable of despeckling echocardiograms (echos) through image-to-image translation in real-time once trained. However, only limited information regarding the quality of denoised echos and explainability of useful GAN components is provided. LÄS MER
4. Brain morphometry in Parkinson’s disease
Master-uppsats,Sammanfattning : Abstract Purpose The purpose of this brain morphometry study was to examine the volumes of different regions of the brain by research participants with Parkinson’s disease. Method To carry out the study, MR (magnetic resonance) images from 956 research participants from the Parkinson’s Progression Markers Initiative (PPMI) were used. LÄS MER
5. Image-driven simulation of brain tumors using a reaction-diffusion mathematical model
Master-uppsats, Linköpings universitet/Avdelningen för medicinsk teknikSammanfattning : Brain tumors pose a big challenge in the field of neuro-oncology. Gliomas are the largest subgroup. Magnetic resonance imaging is a non-invasive tool for detecting and characterizing these tumors. Mathematical models, such as the reaction-diffusion equation, can be used for understanding the intricate behavior of gliomas. LÄS MER