Essays about: "Överförningsinlärning"

Found 3 essays containing the word Överförningsinlärning.

  1. 1. Unsupervised Domain Adaptation for Regressive Annotation : Using Domain-Adversarial Training on Eye Image Data for Pupil Detection

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Erik Zetterström; [2023]
    Keywords : Neural networks; Deep learning; Convolutional neural networks; Transfer learning; Domain adaptation; Unsupervised training; Adversarial training; Keypoint detection; Regression; Neurala nätverk; Djupinlärning; Faltningsnätverk; Överförningsinlärning; Domänadaptering; Oövervakad inlärning; Motstående träning; Nyckelpunktsdetektion; Regression;

    Abstract : Machine learning has seen a rapid progress the last couple of decades, with more and more powerful neural network models continuously being presented. These neural networks require large amounts of data to train them. READ MORE

  3. 2. Evaluation of two CNN models, VGGNet-16 & VGGNet-19, for classification of Alzheimer’s disease in brain MRI scans

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Tim Jonsson; Isabella Tapper; [2020]
    Keywords : ;

    Abstract : Computer-aided-diagnosis (CAD) emerged in the early 1950s and since then CAD has facilitated the diagnosing of many medical conditions and diseases. In particular, CADfor Alzheimer’s disease (AD) has been immensely researched the last decade thanks to advanced neuroimaging techniques such as magnetic resonance imaging (MRI) and positron emission tomography (PET). READ MORE

  4. 3. Mobile Object Detection using TensorFlow Lite and Transfer Learning

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Oscar Alsing; [2018]
    Keywords : cnn; convolutional neural networks; transfer learning; mobile object detection;

    Abstract : With the advancement in deep learning in the past few years, we are able to create complex machine learning models for detecting objects in images, regardless of the characteristics of the objects to be detected. This development has enabled engineers to replace existing heuristics-based systems in favour of machine learning models with superior performance. READ MORE