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Sun, Wei (author)
This work applies keypoint detection method to solve gate recognition problem. Unlike regular object detection task, gate recognition problem is made difficult by the fact that gate is empty wireframe which means that the object surrounded by gate-edge is not relevant and should not be taken into consideration when detecting. However, regular...
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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Claes, Jochem (author)
The Low Earth Orbit (LEO) region has been attractive to many space agencies and organisations because of its ease of access and the ideal opportunity for remote sensing. Due to the low altitudes, a satellite's orbital state is highly affected by the atmospheric drag force acting on the satellite's body. The largest variation in this drag force...
master thesis 2019
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van der Meer, Remco (author)
Recent works have shown that neural networks can be employed to solve partial differential equations, bringing rise to the framework of physics informed neural networks.The aim of this project is to gain a deeper understanding of these novel methods, and to use these insights to further improve them. We show that solving a partial differential...
master thesis 2019
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Hoogendoorn, Jasper (author)
In this thesis, we study the sequential Monte Carlo method for training neural networks in the context of time series forecasting. Sequential Monte Carlo can be particularly useful in problems in which the data is sequential, noisy and non-stationary. We compare this algorithm against a gradient-based method known as stochastic gradient descent ...
master thesis 2019
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SHARMA, Sparsh (author)
The increasing complexity of mechanical systems has resulted in an increased usage and dependence on data driven modelling techniques in order to obtain simple yet accurate models of these systems. Neural networks have emerged as a popular modelling choice due to their proven ability to learn complex nonlinear relationships between inputs and...
master thesis 2019
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Miedema, Rene (author)
In the field of computational neuroscience, complex mathematical models are used to replicate brain behavior with the goal of understanding the biological processes involved. The simulation of such models are computationally expensive and therefore, in recent years, high-performance computing systems have been identified as a possible solution...
master thesis 2019
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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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Irawan, Angga (author)
Controller synthesis techniques based on symbolic models or discrete abstractions are becoming increasingly attractive as they allow for synthesizing correct-by-design controllers of general nonlinear systems under complex behavioral requirements. However, its immense size as the consequence of the state-space explosion prohibits the approach to...
master thesis 2018
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Koeten, Vincent (author)
Current hospital protocols dictate patients be turned at least every three hours in the effort of preventing pressure ulcers. To reduce the workload of nurses, Momo Medical has created an embedded sensing device to track the patient's posture and notify nurses when it is time to turn them. The challenge presented and the focus of this thesis is...
master thesis 2018
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Tijink, Jan (author)
master thesis 2018
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Kiefer, Joshua (author)
More than half a century after the first application of composite materials in aircraft, the accurate prediction of their failure remains a pressing and unresolved issue. Another important limitation continues to be the low transverse strength of unidirectional composite plies, which can lead to premature failure in common laminates such as the...
master thesis 2018
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Zhong, Shijian (author)
The Train Maintenance Scheduling Problem (TMSP) is a real-world problem that aims at complete maintenance tasks of trains by scheduling their activities on a service site. Common methods of constructing optimal solutions to this problem are difficult as the problem consists of several highly-related sub-problems. Currently, NS is using a lo- cal...
master thesis 2018
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Chen, Shuang (author)
master thesis 2018
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Zhou, Lizhongyang (author)
It is desirable to predict construction cost with a high level of accuracy in the early phase to compare the budgetary with feasibility determinations. Additionally, it is required to be as quick as possible. However, the accuracy of the cost estimation depends on the design details which are extremely limited in such an early phase, rendering...
master thesis 2018
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Haenen, Anner (author)
Heerema Marine Contractors (HMC) is a contractor in the international offshore oil, gas and renewables industry. It is specialized in transporting, installing and removing large offshore facilities. HMC operates three crane vessels. Two of which are semi-submersibles (Thialf and Balder), the other is the monohull Aegir. A third semi-submersible,...
master thesis 2018
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Kolthof, Daan (author)
In several machine learning problems, a relatively small subproblem is present in which combinations of (negating) objects or structures result in a negation or otherwise other classification compared to when these (negating) objects are not present. To be more specific, a variant of the XOR problem is present in a small amount of objects in...
master thesis 2018
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Smyrniou, Eleni (author)
Constitutive models are one of the main building blocks of the Finite Element Analysis that nowadays is used in almost every geotechnical engineering project. Thus, finding realistic stress-strain behaviour models has been one of the main fields of research in Geotechnical Engineering. However, constitutive equations have become increasingly...
master thesis 2018
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Saito, Taiyo (author)
The aim of this thesis is to forecast the evolution of the prepayment rate in a mortgage portfolio. In the Netherlands, people with a loan have the possibility to repay (part of) their outstanding loan before the due date. These prepayments make the length of the portfolio of loans stochastic, which creates problems in the refinancing policy of...
master thesis 2018
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Bergwerf, Herman (author)
The goal of this thesis is to find an automated method that can trace all nerve fibers in bright-field images of skin tissue. This is an important step towards the automated quantification of intra-epidermal nerve fiber density, an important biomarker in the diagnosis of small-fiber neuropathy.
Deep learning is a popular new field of...
bachelor thesis 2018
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