Sökning: "convolutional neural network CNN"

Visar resultat 1 - 5 av 24 avhandlingar innehållade orden convolutional neural network CNN.

  1. 1. 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

  2. 2. 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. 3. 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. 4. Automated Gravel Road Condition Assessment : A Case Study of Assessing Loose Gravel using Audio Data

    Författare :Nausheen Saeed; Moudud Alam; Roger G. Nyberg; Diala Jomaa; Mirka Kans; Högskolan Dalarna; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; Gravel roads; road maintenance; convolutional neural network CNN ; SVM; decision trees; ensemble bagged trees; GoogLeNet; ResNet50; ResNet18; sound analysis;

    Sammanfattning : Gravel roads connect sparse populations and provide highways for agriculture and the transport of forest goods. Gravel roads are an economical choice where traffic volume is low. In Sweden, 21% of all public roads are state-owned gravel roads, covering over 20,200 km. LÄS MER

  5. 5. Drill Failure Detection based on Sound using Artificial Intelligence

    Författare :Thanh Tran; Jan Thim; Sebastian Bader; Kalle Åström; Mittuniversitetet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Convolutional neural network; machine failure detection; Mel-spectrogram; long short-term memory; sound signal processing;

    Sammanfattning : In industry, it is crucial to be able to detect damage or abnormal behavior in machines. A machine's downtime can be minimized by detecting and repairing faulty components of the machine as early as possible. It is, however, economically inefficient and labor-intensive to detect machine fault sounds manual. LÄS MER