Search for dissertations about: "Convolutional Neural Networks"

Showing result 1 - 5 of 17 swedish dissertations containing the words Convolutional Neural Networks.

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

    University dissertation from Uppsala : Acta Universitatis Upsaliensis

    Author : Sajith Kecheril Sadanandan; Uppsala universitet.; Uppsala universitet.; [2017]
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; 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. Water–fat separation in magnetic resonance imaging and its application in studies of brown adipose tissue

    University dissertation from Uppsala : Acta Universitatis Upsaliensis

    Author : Jonathan Andersson; Uppsala universitet.; [2019]
    Keywords : MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; 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

  3. 3. Convolutional Network Representation for Visual Recognition

    University dissertation from KTH Royal Institute of Technology

    Author : Ali Sharif Razavian; KTH.; [2017]
    Keywords : 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

  4. 4. Modeling Music Studies of Music Transcription, Music Perception and Music Production

    University dissertation from Stockholm : KTH Royal Institute of Technology

    Author : Anders Elowsson; KTH.; [2018]
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Music Information Retrieval; MIR; Music; Music Transcription; Music Perception; Music Production; Tempo Estimation; Beat Tracking; Polyphonic Pitch Tracking; Polyphonic Transcription; Music Speed; Music Dynamics; Long-time average spectrum; LTAS; Algorithmic Composition; Deep Layered Learning; Convolutional Neural Networks; Rhythm Tracking; Ensemble Learning; Perceptual Features; Representation Learning;

    Abstract : This dissertation presents ten studies focusing on three important subfields of music information retrieval (MIR): music transcription (Part A), music perception (Part B), and music production (Part C).In Part A, systems capable of transcribing rhythm and polyphonic pitch are described. READ MORE

  5. 5. Improving Multi-Atlas Segmentation Methods for Medical Images

    University dissertation from ; Chalmers tekniska högskola; Gothenburg

    Author : Jennifer Alvén; [2017]
    Keywords : 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;

    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