Search for dissertations about: "computer vision segmentation"

Showing result 1 - 5 of 70 swedish dissertations containing the words computer vision segmentation.

  2. 1. Deep Learning Methods for Classification of Gliomas and Their Molecular Subtypes, From Central Learning to Federated Learning

    Author : Muhaddisa Barat Ali; Chalmers tekniska högskola; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; glioma subtype classification; convolutional autoencoder; convolutional NN; multi-stream U-Net.; CycleGAN; 1p 19q codeletion; federated learning; IDH mutation; generative adversarial network; Deep learning;

    Abstract : The most common type of brain cancer in adults are gliomas. Under the updated 2016 World Health Organization (WHO) tumor classification in central nervous system (CNS), identification of molecular subtypes of gliomas is important. READ MORE

  4. 2. Discrete Scale-Space Theory and the Scale-Space Primal Sketch

    Author : Tony Lindeberg; Jan-Olof Eklundh; Jan. J Koenderink; KTH; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Computer vision; low-level processing; scale-space; diffusion; Gaussian filtering; discrete smoothing; primal sketch; segmentation; descriptive elements; scale detection; image structure; focus-of-attention; tuning low-level processing; blob detection; edge detection; edge focusing; histogram analysis; junction classification; perceptual grouping; texture analysis; critical points; classification of blob events; bifurcations; drift velocity; density of local extrema; multi-scale representation; digital signal processing; Computer Science; Datalogi;

    Abstract : This thesis, within the subfield of computer science known as computer vision, deals with the use of scale-space analysis in early low-level processing of visual information. The main contributions comprise the following five subjects:The formulation of a scale-space theory for discrete signals. READ MORE

  5. 3. Higher-Order Regularization in Computer Vision

    Author : Johannes Ulén; Matematik LTH; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Computer Vision; Regularization; Segmentation; Dense Stereo;

    Abstract : At the core of many computer vision models lies the minimization of an objective function consisting of a sum of functions with few arguments. The order of the objective function is defined as the highest number of arguments of any summand. READ MORE

  6. 4. Visual Attention in Active Vision Systems : Attending, Classifying and Manipulating Objects

    Author : Babak Rasolzadeh; Jan-Olof Eklundh; Ales Leonardis; KTH; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; visual attention; saliency map; compter vision; robotics; active vision; machine learning;

    Abstract : This thesis has presented a computational model for the combination of bottom-up and top-down attentional mechanisms. Furthermore, the use for this model has been demonstrated in a variety of applications of machine and robotic vision. READ MORE

  7. 5. Action in Mind : A Neural Network Approach to Action Recognition and Segmentation

    Author : Zahra Gharaee; Kognitiv modellering; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Action recognition; motion perception; cognitive robotics; hierarchical models; self-organizing neural networks; growing grids; attention;

    Abstract : Recognizing and categorizing human actions is an important task with applications in various fields such as human-robot interaction, video analysis, surveillance, video retrieval, health care system and entertainment industry.This thesis presents a novel computational approach for human action recognition through different implementations of multi-layer architectures based on artificial neural networks. READ MORE