Sökning: "image segmentation"
Visar resultat 1 - 5 av 231 uppsatser innehållade orden image segmentation.
- Master-uppsats, KTH/Skolan för kemi, bioteknologi och hälsa (CBH)
Sammanfattning : Even with the recent advances of deep learning pushing the field of medical image analysis further than ever before, progress is still slow due to limited availability of annotated data. There are multiple reasons for this, but perhaps the most prominent one is the amount of time manual annotation of medical images takes. LÄS MER
- Kandidat-uppsats, Högskolan i Gävle/Avdelningen för datavetenskap och samhällsbyggnad; Högskolan i Gävle/Avdelningen för datavetenskap och samhällsbyggnad
Sammanfattning : Automated pattern recognition of stone walls, within both point cloud and image processing, can help identify previously inaccessible areas than with only image pro-cessing. This is important as stone walls are biotopes and serve as structures and have ecological functions for both plants and animals. LÄS MER
- Master-uppsats, Linköpings universitet/Avdelningen för kardiovaskulär medicin
Sammanfattning : A personalized cardiovascular lumped parameter model of the left-sided heart and thesystemic circulation has been developed by the cardiovascular medicine research groupat Linköping University. It provides information about hemodynamics, some of whichcould otherwise only have been retrieved by invasive measurements. LÄS MER
4. Mathematical Analysis of Intensity Based Segmentation Algorithms with Implementations on Finger Images in an Uncontrolled EnvironmentKandidat-uppsats, Mälardalens högskola/Akademin för utbildning, kultur och kommunikation
Sammanfattning : The main task of this thesis is to perform image segmentation on images of fingers to partition the image into two parts, one with the fingers and one with all that is not fingers. First, we present the theory behind several well-used image segmentation methods, such as SNIC superpixels, the k-means algorithm, and the normalised cut algorithm. LÄS MER
5. Improving 3D Point Cloud Segmentation Using Multimodal Fusion of Projected 2D Imagery Data : Improving 3D Point Cloud Segmentation Using Multimodal Fusion of Projected 2D Imagery DataMaster-uppsats, Linköpings universitet/Datorseende
Sammanfattning : Semantic segmentation is a key approach to comprehensive image data analysis. It can be applied to analyze 2D images, videos, and even point clouds that contain 3D data points. LÄS MER