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Friđriksdóttir, Esther (author)
Physical activity and mobility are important indicators of the recovery process of patients in the general ward of the hospital. Currently, monitoring mobility of hospitalized patients relies largely on direct observation from the caregivers. Accelerometers have the potential to quantify physical activity of patients objectively and without...
master thesis 2019
document
Garbacz, Mateusz (author)
Being capable to foresee the future of a given financial asset as an investor, may lead to significant economic profits. Therefore, stock market prediction is a field that has been extensively developed by numerous researchers and companies. Recently, however, a new branch of financial assets has emerged, namely cryptocurrencies. As a...
master thesis 2018
document
Kapadia, Husain (author)
Listening in noise is a challenging problem that affects the hearing capability of not only normal hearing but especially hearing impaired people. Since the last four decades, enhancing the quality and intelligibility of noise corrupted speech by reducing the effect of noise has been addressed using statistical signal processing techniques as...
master thesis 2019
document
Samiotis, Ioannis Petros (author)
Side-Channel Attacks, are a prominent type of attacks, used to break cryptographic implementations on a computing system. They are based on information "leaked" by the hardware of a computing system, rather than the encryption algorithm itself. Recent studies showed that Side-Channel Attacks can be performed using Deep Learning models. In this...
master thesis 2018
document
van Hilten, Arno (author)
Cardiovascular diseases and stroke are currently the leading causes of death worldwide. Atherosclerotic plaque is a mostly asymptotic vascular disease, but rupture of an atherosclerotic plaque in the carotid artery could lead to stroke. Automated segmentation of plaque components could help improve risk assessment by producing fast and reliable...
master thesis 2018
document
Dhar, Aniket (author)
Convolutional neural networks are showing incredible performance in image classification, segmentation, object detection and other computer vision applications in recent years. But they lack understanding of affine transformations to input data. In this work, we introduce rotational invariant<br/>convolutional neural networks that learn...
master thesis 2018
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Pop, Marius (author)
Security has become ever more important in today's quickly growing digital world as the number of digital assets has quickly grown. Our thesis focuses on devices that compute a secure cryptographic operation such that information can be communicated or authenticated. The attack vector utilized is known as Profiled Side-Channel Analysis (SCA)...
master thesis 2019
document
IJzermans, Erik (author)
The newest generation of aircraft has seen a strong increase in sensor data generated on-board. The available data has the potential to indicate the health state of individual components based on which their maintenance requirements can be determined, a maintenance strategy called Condition Based Maintenance. Predictive Maintenance is a specific...
master thesis 2018
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Graur, Dan (author)
Given the increasing popularity of Machine Learning, and the ever increasing need to solve larger and more complex learning challenges, it is unsurprising that numerous distributed learning strategies have been brought forward in recent years, along with many large scale Machine Learning frameworks. It is however unclear how well these...
master thesis 2019
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Arnaoutis, Vasos (author)
Deep Learning performance dependents on the application and methodology. Neural Networks with convolutional layers have been a great success in multiple tasks trained under Supervised Learning algorithms. For higher dimensional problems, the selection of a deep network architecture can significantly improve the accuracy of the network, however...
master thesis 2019
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Elghlan, Faris (author)
This M.Sc. thesis report investigates the application of one-class classification techniques to complex high-dimensional data. The aim of a one-class classifier is to separate target data from non-target data, but only a dataset containing target data is available for training. The issue with high-dimensional data is that it is difficult to...
master thesis 2019
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Rao, Shashank (author)
Sleep is a natural state of our mind and body during which our muscles heal and our memories are consolidated. It is such a habitual phenomenon that we have been viewing it as another ordinary task in our day-to-day life. However, owing to the current fast-paced, technology-driven generation, we are letting ourselves be sleep-deprived, giving...
master thesis 2018
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Sadon, A.P.J. (author)
Het onderzoek heeft zich gericht op de ontwikkeling van een Semantisch Connectionistisch Redeneersysteem (SCORE). SCORE kan de basis vormen voor een volwaardig expertsysteem. De, voor een expertsysteem van elementair belang zijnde, fundamentele inferentie principes, kennisacquisitie principes en kennisrepresentatievormen hebben in SCORE de...
master thesis 1990
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Helmiriawan, Helmi (author)
Modern refineries typically use a high number of sensors that generate an enormous amount of data about the condition of the plants. This generated data can be used to perform predictive maintenance, an approach to predict impending failures and mitigate downtime in refineries. This research analyzes the scalability of machine learning methods...
master thesis 2018
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Jargot, Dominik (author)
Nowadays, autonomous driving is a trending topic in the automotive field. One of the most crucial challenges of autonomous driving research is environment perception. Currently, many techniques achieve satisfactory performance in 2D object detection using camera images. Nevertheless, such 2D object detection might be not sufficient for autonomous...
master thesis 2019
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