Search for dissertations about: "convolutional neural networks"

Showing result 1 - 5 of 34 swedish dissertations containing the words convolutional neural networks.

  1. 1. Deep Neural Networks and Image Analysis for Quantitative Microscopy

    Author : Sajith Kecheril Sadanandan; Carolina Wählby; Petter Ranefall; Ewert Bengtsson; Jeroen van der Laak; Uppsala universitet; []
    Keywords : ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Deep neural networks; convolutional neural networks; image analysis; quantitative microscopy; bright-field microscopy; Computerized Image Processing; Datoriserad bildbehandling;

    Abstract : Understanding biology paves the way for discovering drugs targeting deadly diseases like cancer, and microscopy imaging is one of the most informative ways to study biology. However, analysis of large numbers of samples is often required to draw statistically verifiable conclusions. READ MORE

  2. 2. Machine Learning Methods for Image Analysis in Medical Applications, from Alzheimer's Disease, Brain Tumors, to Assisted Living

    Author : Chenjie Ge; Chalmers University of Technology; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; glioma subtype classification; deep learning; spiking neural networks; recurrent convolutional networks; machine learning; semi-supervised learning; fall detection; Alzheimer s disease detection; visual prosthesis; generative adversarial networks; convolutional neural networks;

    Abstract : Healthcare has progressed greatly nowadays owing to technological advances, where machine learning plays an important role in processing and analyzing a large amount of medical data. This thesis investigates four healthcare-related issues (Alzheimer's disease detection, glioma classification, human fall detection, and obstacle avoidance in prosthetic vision), where the underlying methodologies are associated with machine learning and computer vision. READ MORE

  3. 3. Water–fat separation in magnetic resonance imaging and its application in studies of brown adipose tissue

    Author : Jonathan Andersson; Joel Kullberg; Håkan Ahlström; Mark Lubberink; Kerstin Lagerstrand; Uppsala universitet; []
    Keywords : MEDICAL AND HEALTH SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; TEKNIK OCH TEKNOLOGIER; MEDICIN OCH HÄLSOVETENSKAP; ENGINEERING AND TECHNOLOGY; MEDICAL AND HEALTH SCIENCES; brown adipose tissue; magnetic resonance imaging; water–fat signal separation; graph-cut; positron emission tomography; 18F-fludeoxyglucose; infrared thermography; machine learning; artificial neural networks; deep learning; convolutional neural networks; Radiology; Radiologi;

    Abstract : Virtually all the magnetic resonance imaging (MRI) signal of a human originates from water and fat molecules. By utilizing the property chemical shift the signal can be separated, creating water- and fat-only images. READ MORE

  4. 4. DeepMaker : Customizing the Architecture of Convolutional Neural Networks for Resource-Constrained Platforms

    Author : Mohammad Loni; Mikael Sjödin; Masoud Daneshtalab; Franz Pernkopf; Mälardalens högskola; []

    Abstract : Convolutional Neural Networks (CNNs) suffer from energy-hungry implementation due to requiring huge amounts of computations and significant memory consumption. This problem will be more highlighted by the proliferation of CNNs on resource-constrained platforms in, e.g., embedded systems. READ MORE

  5. 5. Convolutional Network Representation for Visual Recognition

    Author : Ali Sharif Razavian; Atsuto Maki; Stefan Carlsson; Josephine Sullivan; Josef Sivic; KTH; []
    Keywords : ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Convolutional Network; Visual Recognition; Transfer Learning; Datalogi; Computer Science;

    Abstract : Image representation is a key component in visual recognition systems. In visual recognition problem, the solution or the model should be able to learn and infer the quality of certain visual semantics in the image. READ MORE