Sökning: "Semantic segmentation"
Visar resultat 1 - 5 av 31 avhandlingar innehållade orden Semantic segmentation.
1. Data-Efficient Learning of Semantic Segmentation
Sammanfattning : Semantic segmentation is a fundamental problem in visual perception with a wide range of applications ranging from robotics to autonomous vehicles, and recent approaches based on deep learning have achieved excellent performance. However, to train such systems there is in general a need for very large datasets of annotated images. LÄS MER
2. Improving Multi-Atlas Segmentation Methods for Medical Images
Sammanfattning : Semantic segmentation of organs or tissues, i.e. delineating anatomically or physiologically meaningful boundaries, is an essential task in medical image analysis. One particular class of automatic segmentation algorithms has proved to excel at a diverse set of medical applications, namely multi-atlas segmentation. LÄS MER
3. End-to-End Learning of Deep Structured Models for Semantic Segmentation
Sammanfattning : The task of semantic segmentation aims at understanding an image at a pixel level. This means assigning a label to each pixel of an image, describing the object it is depicting. LÄS MER
4. Resource efficient automatic segmentation of medical images
Sammanfattning : Cancer is one of the leading causes of death worldwide. In 2020, there were around 10 million cancer deaths and nearly 20 million new cancer cases in the world. Radiation therapy is essential in cancer treatments because half of the cancer patients receive radiation therapy at some point. LÄS MER
5. Unsupervised construction of 4D semantic maps in a long-term autonomy scenario
Sammanfattning : Robots are operating for longer times and collecting much more data than just a few years ago. In this setting we are interested in exploring ways of modeling the environment, segmenting out areas of interest and keeping track of the segmentations over time, with the purpose of building 4D models (i.e. LÄS MER