Searched for: subject:"Machine%5C+Learning"
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van Laar, Patrick (author)
New measures have to be taken to combat fatalities caused by traffic accidents. Intelligent vehicles have the potential to increase safety, but depend heavily on their automated perception ability.
Acoustic perception, an unused sensing modality in this field, has potential for the detection of nearby vehicles, an ability both human drivers...
master thesis 2019
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van Korlaar, Arent (author)
Turbulence closure models will continue to be necessary in order to perform computationally affordable simulations in the foreseeable future. It is expected that Reynolds-averaged Navier-Stokes (RANS) turbulence models will still be useful with the further development of the more accurate, but computationally expensive large eddy simulation (LES...
master thesis 2019
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Nikolopoulos, Dionysis (author)
There is an increasing attention towards link prediction in complex networks both in physical and computer science communities. Particularly Online Social Networks (OSNs) are
becoming the most popular platforms for information sharing, content creation and communication between users on the Internet. However, most of the research was done...
master thesis 2019
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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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Koch, Mike (author)
The air cargo industry is a challenging environment due to the high competition between the stakeholders involved. This demands, as example, high efficiency from cargo airlines. Efficiency can be ensured by designing loading strategies that fully exploit the available cargo volume. Unknowns in the booking dimensions and flight information make...
master thesis 2019
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Leunge, Laurens (author)
In the Netherlands, robust dike and dam design is a major concern in the context of flood defence. Due to heterogeneity of the subsoil on which these structures are founded, the validity range of in situ tests decreases drastically. Consequently, large uncertainties regarding spatial variation of soil stratification and soil layer parameters are...
master thesis 2019
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de Jong, Tjitte (author)
A high drop-out rate is present during current-day air traffic controller (ATCo) training, because the required expertise level is not reached. The determination of the expertise level of ATCo students is currently performed using subjective assessments at a late stage in the training by means of high-fidelity simulator sessions. It is desired...
master thesis 2019
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van Dijk, Mick (author)
Global medical use of azole antifungals and echinocandins has led to an enormous increase in resistant Candida species, that are most commonly associated with fungal infections. A possible mechanism causing resistance are single or simultaneous point mutations in the genes responsible for encoding antifungal target enzymes. The aim of...
master thesis 2019
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Vaporidis, Dimitrios-Marios (author)
In this Master Thesis project, the objective is to study how can Supervised Machine Learning be used to detect text-based rumours for humanitarian activities in Twitter. A model was developed in this project in order to classify a tweet at question whether is a rumour or not and whether is relevant to humanitarian activities or not. The findings...
master thesis 2019
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van Rooijen, Sjoerd (author)
In the upcoming years, en route airspace capacity will be limited by air traffic controller workload, requiring the introduction of automation to assist controllers with conflict detection and resolution. However, acceptance is considered to be one of the main obstacles in the introduction of novel automation. Individual-sensitive automation has...
master thesis 2019
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Husić, Ajdin (author)
The novelty-raahn algorithm has been shown to effectively learn a desired behavior from raw inputs by connecting an autoencoder with a Hebbian network. Hebbian learning is compelling for its biological plausibility and simplicity. It changes the weight of a connection based only on the activations of neurons it connects, and can effectively...
master thesis 2018
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Gulikers, Tom (author)
Engineering fields such as aerospace rely heavily on the Finite Element Method (FEM) as a modelling tool. In combination with the scale and complexity of the structures typically involved here, computational cost remains a traditional issue. To perform FEM analyses of such structures efficiently nonetheless, engineers rely on techniques such as...
master thesis 2018
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Milias, Vasileios (author)
The digital representations of physical places, known as Points-Of-Interest (POIs), have been the core element of various studies and platforms such as online mapping services (e.g. Google Maps) and location based social networks (e.g. Foursquare). The use of POIs as proxies of the real-world-places facilitates the study of places, urban...
master thesis 2018
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Koolen, Sven (author)
Icing conditions are some of the critical operating phenomena that an aircraft engine can encounter within its flight envelope.22,000 feet is recognized in the industry as the upper limit for the existence of super-cooled liquid water. Above this level, the particles are no longer in liquid water form, but rather ice crystals, snowflakes,...
master thesis 2018
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Strijbis, Victor (author)
Introduction:  Despite the vast amount of optimization algorithms, radiotherapy treatment planning remains a manual, time-consuming and iterative process. To increase plan standardization, we clinically use Pinnacle's autoplanner for several disease sites. However, this introduces new challenges: first, the autoplanner is not perfect and still...
master thesis 2018
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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
convolutional neural networks that learn...
master thesis 2018
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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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Jacobs, Freek (author)
Machine learning applications are increasingly being implemented in socio-technical safety-critical systems, but the safety of these applications is not well understood. This thesis used a mixed-method design and applied four methods to explore the field of machine learning and safety. With the results of these four methods, a framework was...
master thesis 2018
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Soto Muñoz Ledo, Sergio (author)
As the elderly world population increases, caregivers are switching to remote care and monitoring solutions to enable their patients to live autonomously at home for as long as possible. Such services are based on detecting and recognizing Activities of Daily Living (ADL) by using diverse types of sensors at the elder's home that transmit...
master thesis 2018
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Adhikari, Ajaya (author)
Machine Learning (ML) is a rapidly growing field. There has been a surge of complex black-box models with high performance. On the other hand, the application of these models especially in high-risk domains is more stagnant due to lack of transparency and trust in these black-box models. There is a disconnect between the black-box character of...
master thesis 2018
Searched for: subject:"Machine%5C+Learning"
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