Sökning: "Convolutional neural networks CNN"

Visar resultat 1 - 5 av 20 avhandlingar innehållade orden Convolutional neural networks CNN.

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

    Författare :Chenjie Ge; Chalmers tekniska högskola; []
    Nyckelord :MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; convolutional neural networks; Alzheimer s disease detection; machine learning; deep learning; fall detection; glioma subtype classification; generative adversarial networks; recurrent convolutional networks; spiking neural networks; visual prosthesis; semi-supervised learning;

    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

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

    Författare :Mohammad Loni; Mikael Sjödin; Masoud Daneshtalab; Franz Pernkopf; Mälardalens högskola; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Computer Science; datavetenskap;

    Sammanfattning : 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. LÄS MER

  4. 3. Pith location and annual ring detection for modelling of knots and fibre orientation in structural timber : A Deep-Learning-Based Approach

    Författare :Tadios Habite; Anders Olsson; Osama Abdeljaber; Jan Oscarsson; Welf Löwe; Julie Cool; Linnéuniversitetet; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Sawn timber; Pith location; Deep learning; Artificial neural networks; Convolutional neural network; Conditional generative adversarial network; Knot detection; Knot modelling; Knot reconstruction; Fibre orientation; Annual ring profile; Byggteknik; Civil engineering;

    Sammanfattning : Detection of pith, annual rings and knots in relation to timber board cross-sections is relevant for many purposes, such as for modelling of sawn timber and for real-time assessment of strength, stiffness and shape stability of wood materials. However, the methods that are available and implemented in optical scanners today do not always meet customer accuracy and/or speed requirements. LÄS MER

  5. 4. 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

  7. 5. 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