Search for dissertations about: "Convolutional Neural Networks"
Showing result 1 - 5 of 72 swedish dissertations containing the words Convolutional Neural Networks.
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1. G-equivariant convolutional neural networks
Abstract : Over the past decade, deep learning has revolutionized industry and academic research. 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, in some cases reaching superhuman levels of performance. READ MORE
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2. Deep Neural Networks and Image Analysis for Quantitative Microscopy
Abstract : Understanding biology paves the way for discovering drugs targeting deadly diseases like cancer, and microscopy imaging is one of the most informative ways to study biology. However, analysis of large numbers of samples is often required to draw statistically verifiable conclusions. READ MORE
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3. 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
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4. Machine Learning Methods for Image Analysis in Medical Applications, from Alzheimer's Disease, Brain Tumors, to Assisted Living
Abstract : 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. READ MORE
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5. Water–fat separation in magnetic resonance imaging and its application in studies of brown adipose tissue
Abstract : 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. READ MORE