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den Boer, Hans (author)
Recently, interest in the use of deep learning technology for RF applications has increased. However, many of these studies are focused on developing deep learning models for a particular RF application. Therefore this master thesis focuses on the implementation of these kinds of deep learning models by using FPGAs such that these deep learning...
master thesis 2021
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Arif Nurhidayat, Arif (author)
In this thesis, a method to monitor the health condition of railway crossings based on vibration data recorded by the accelerometers installed on the crossing is proposed. Due to various types of trains and other exogenous factors, responses obtained from accelerometers vary, even when the crossing has the same state condition. As a consequence,...
master thesis 2018
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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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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
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Liu, Lu (author)
During the last decades, people detection has received great attention in computer vision and pattern recognition because of its various applications. Though there are thousands of papers provide approaches for people detection, most of them focus on datasets from side view. People detection from overhead cameras, as an important situation for...
master thesis 2018
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Marcelis, N.H.H. (author)
With the performance of current motion planning methods being highly dependent on the quality of the perception system, robust 3D multi-object detection and tracking are vital for autonomous driving applications. Despite all the advancements in 2D and 3D object detectors, robust tracking of pedestrians in dense scenarios is still a challenging...
master thesis 2021
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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
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de Bruijne, Bas (author)
Ground based telescope imaging suffers from interference from the earth’s atmosphere. Fluctuations in the refractive index of the air delay incoming light randomly, resulting in blurred images. A deconvolution from wavefront sensing system is an adaptive optics system that measures the modes in which the light is corrupted (i.e. the wavefront)...
master thesis 2021
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Li, Xinqi (author)
Quantitative cardiac MRI is an increasingly important diagnostic tool for cardiovascular diseases. Yet, it is essential to have correct image registration for good accuracy and precision of quantitative mapping. Registering all baseline images from a quantitative cardiac MRI sequence, however, is nontrivial because the patient is moving, leading...
master thesis 2023
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Basu, Debadeep (author)
This work applies the theory of group equivariance to the domain of video action recognition replacing standard 3Dconvolutions with group convolutions which are equivariant to temporal direction, and multiples of 90-degree spatial rotations. We propose a temporal direction symmetry group T2 and extend the standard planar rotations group to three...
master thesis 2021
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Beekhuizen, Michael (author)
Cardiovascular diseases are one of the primary causes of mortality worldwide. Paroxysmal atrial fibrillation is a specific type that is difficult to detect and diagnose in a short time frame. To overcome this, we investigated if long-term wearable data can be used for the detection of heart diseases. The BigIdeasLab_STEP dataset and long-term...
master thesis 2023
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Vogiatzis, Anastasios (author)
Everything around us is rapidly changing. Whole new blocks of buildings are built, huge infrastructural projects are constructed and so on. Hence, there is a need of a reliable and up-to-date inventory of the area and the objects of interest for mapping and monitoring assets and their changes. An answer of this upcoming need is an automated...
master thesis 2021
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Hommos, Omar (author)
Action recognition continues to receive significant attention from the research community, with new neural network architectures being developed continuously. Optical flow is by far the most popular input motion representation to these architectures, leaving a lot of undiscovered potential for other types of motion representations. Eulerian...
master thesis 2018
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Lelekas, Ioannis (author)
Biological vision adopts a coarse-to-fine information processing pathway, from initial visual detection and binding of salient features of a visual scene, to the enhanced and preferential processing given relevant stimuli. On the contrary, CNNs employ a fine-to-coarse processing, moving from local, edge-detecting filters to more global ones...
master thesis 2020
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van den Berg, Jasper (author)
The traumatic loss of a hand is a horrific experience usually followed by significant psychological, functional and rehabilitation challenges. Even though much progress has been made in the past decades, the prosthetic challenge of restoring the human hand functionality is still far from being achieved. Autonomous prosthetic hands showed...
master thesis 2023
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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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Deichler, Anna (author)
Recently, the AlphaGo algorithm has managed to defeat the top level human player in the game of Go. Achieving professional level performance in the game of Go has long been considered as an AI milestone. The challenging properties of high state-space complexity, long reward horizon and high action branching factor in the game of Go are also...
master thesis 2019
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Gabriel, Luka (author)
Both MRI and CT imaging are commonly used and combined in medical imaging because of their complementary information about soft tissue and bone respectively. However, CT imaging relies on harmful ionizing radiation. Thus medical imaging scientists are working on transferring harmless MRI scans to CT-like images where using deep learning methods...
master thesis 2018
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Lusse, Bryan (author)
Long acquisition times impede the routine clinical use of quantitative magnetic resonance imaging (qMRI). qMRI quantifies meaningful tissue parameters in T1-, T2-, and PD-maps, as opposed to conventional (qualitative) weighted MRI (wMRI), which only visualises contrast between tissues. Although methods exist that generate synthetic wMRI from...
master thesis 2021
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Yin, Yunchao (author)
Coronary artery disease is the most common type of heart disease, which influences 110 million people's health and causes 8.9 million deaths in 2015. Physicians can visualize the lesion in coronary arteries by cardiac angiography (X-ray image) during diagnosis and treatment of coronary artery disease. The pathological findings in cardiac...
master thesis 2018
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