Sökning: "Convolutional Neural Networks"

Visar resultat 1 - 5 av 20 avhandlingar innehållade orden Convolutional Neural Networks.

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

    Författare :Chenjie Ge; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; 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;

    Sammanfattning : 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. LÄS MER

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

    Detta är en avhandling från Uppsala : Acta Universitatis Upsaliensis

    Författare :Jonathan Andersson; Joel Kullberg; Håkan Ahlström; Mark Lubberink; Kerstin Lagerstrand; [2019]
    Nyckelord :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;

    Sammanfattning : 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. LÄS MER

  3. 3. Convolutional Network Representation for Visual Recognition

    Detta är en avhandling från KTH Royal Institute of Technology

    Författare :Ali Sharif Razavian; Atsuto Maki; Stefan Carlsson; Josephine Sullivan; Josef Sivic; [2017]
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Convolutional Network; Visual Recognition; Transfer Learning; Datalogi; Computer Science;

    Sammanfattning : 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. LÄS MER

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

    Detta är en avhandling från Stockholm : KTH Royal Institute of Technology

    Författare :Anders Elowsson; Anders Friberg; Pawel Herman; Anders Askenfelt; Gerhard Widmer; [2018]
    Nyckelord :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;

    Sammanfattning : 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. LÄS MER

  5. 5. Combining Shape and Learning for Medical Image Analysis

    Detta är en avhandling från Gothenburg : Chalmers tekniska högskola

    Författare :Jennifer Alvén; [2020]
    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