Search for dissertations about: "conditional random fields"
Showing result 1 - 5 of 8 swedish dissertations containing the words conditional random fields.
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1. Combining Shape and Learning for Medical Image Analysis
Abstract : Automatic methods with the ability to make accurate, fast and robust assessments of medical images are highly requested in medical research and clinical care. Excellent automatic algorithms are characterized by speed, allowing for scalability, and an accuracy comparable to an expert radiologist. READ MORE
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2. Improving Multi-Atlas Segmentation Methods for Medical Images
Abstract : 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. READ MORE
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3. Modeling of bacterial DNA patterns important in horizontal gene transfer using stochastic grammars
Abstract : DNA contains genes which carry the blueprints for all processes necessary to maintain life. In addition to genes, DNA also contains a wide range of functional patterns, which governs many of these processes. These functional patterns have typically a high variability, both within and between species, which makes them hard to detect. READ MORE
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4. End-to-End Learning of Deep Structured Models for Semantic Segmentation
Abstract : 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. READ MORE
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5. Geometric Supervision and Deep Structured Models for Image Segmentation
Abstract : The task of semantic segmentation aims at understanding an image at a pixel level. Due to its applicability in many areas, such as autonomous vehicles, robotics and medical surgery assistance, semantic segmentation has become an essential task in image analysis. READ MORE