Search for dissertations about: "Convolutional neural network"
Showing result 1 - 5 of 60 swedish dissertations containing the words Convolutional neural network.
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1. Convolutional Network Representation for Visual Recognition
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
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2. Network Parameterisation and Activation Functions in Deep Learning
Abstract : Deep learning, the study of multi-layered artificial neural networks, has received tremendous attention over the course of the last few years. Neural networks are now able to outperform humans in a growing variety of tasks and increasingly have an impact on our day-to-day lives. READ MORE
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3. Deep Learning Methods for Classification of Glioma and its Molecular Subtypes
Abstract : Diagnosis and timely treatment play an important role in preventing brain tumor growth. Clinicians are unable to reliably predict LGG molecular subtypes from magnetic resonance imaging (MRI) without taking biopsy. Accurate diagnosis prior to surgery would be important. READ MORE
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4. Pith location and annual ring detection for modelling of knots and fibre orientation in structural timber : A Deep-Learning-Based Approach
Abstract : 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. READ MORE
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5. Mathematical Foundations of Equivariant Neural Networks
Abstract : Deep learning has revolutionized industry and academic research. Over the past decade, neural networks have been used to solve a multitude of previously unsolved problems and to significantly improve the state of the art on other tasks. However, training a neural network typically requires large amounts of data and computational resources. READ MORE