Sökning: "Convolutional Neural Networks"

Visar resultat 16 - 20 av 72 avhandlingar innehållade orden Convolutional Neural Networks.

1. 16. Combining Shape and Learning for Medical Image Analysis

   Författare :Jennifer Alvén; Chalmers tekniska högskola; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; feature-based registration; convolutional neural networks; conditional random fields; medical image segmentation; random decision forests; machine learning; multi-atlas segmentation; medical image registration; shape models;

   Sammanfattning : 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. LÄS MER

3. 17. Improving Multi-Atlas Segmentation Methods for Medical Images

   Författare :Jennifer Alvén; Chalmers tekniska högskola; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Supervised learning; semantic segmentation; multi-atlas segmentation; conditional random fields; label fusion; feature-based registration; image registration; random decision forests; convolutional neural networks; medical image segmentation;

   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

4. 18. End-to-End Learning of Deep Structured Models for Semantic Segmentation

   Författare :Måns Larsson; Chalmers tekniska högskola; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Semantic segmentation; deep structured models; supervised learning; convolutional neural networks; conditional random fields;

   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

5. 19. Geometric Supervision and Deep Structured Models for Image Segmentation

   Författare :Måns Larsson; Chalmers tekniska högskola; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; conditional random fields; convolutional neural networks; deep structured models; Semantic segmentation; self-supervised learning; supervised learning; semi-supervised learning;

   Sammanfattning : 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. LÄS MER

7. 20. On sparse voxel DAGs and memory efficient compression of surface attributes for real-time scenarios

   Författare :Dan Dolonius; Chalmers tekniska högskola; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; directed acyclic graph; surface properties; neural networks; voxel; compression; spherical gaussians; light field; octree; filtering; geometry;

   Sammanfattning : The general shape of a 3D object can expeditiously be represented as, e.g., triangles or voxels, while smaller-scale features usually are parameterized over the surface of the object. LÄS MER