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Betting, Jan-Harm (author)
The movement of whiskers in head-fixed mice is of high interest for neurological research, as it allows scientists to learn more about learning processes during active touch. However, manual tracking of whiskers in thousands of frames is not feasible, and reliable tracking of individual whiskers is not possible with the best current software...
master thesis 2018
document
Kaandorp, Mikael (author)
The application of machine learning algorithms as data-driven turbulence modelling tools for Reynolds Averaged Navier-Stokes (RANS) simulations is presented. A novel machine learning algorithm, called the Tensor Basis Random Forest (TBRF) is introduced, which is able to predict the Reynolds stress anisotropy tensor. The algorithm is trained on...
master thesis 2018
document
Kisantal, Máté (author)
Safe navigation in a cluttered environment is a key capability for the autonomous operation of Micro Aerial Vehicles (MAVs). This work explores a (deep) Reinforcement Learning (RL) based approach for monocular vision based obstacle avoidance and goal directed navigation for MAVs in cluttered environments. We investigated this problem in the...
master thesis 2018
document
Sulzer, Raphael (author)
The seismic building structural type (SBST) reflects the main load-bearing structure of a building and therefore its behaviour under seismic load. For numerous areas in earthquake prone regions this information is outdated, unavailable, or simply not existent. Traditional methods to gather this information, such as building-by-building...
master thesis 2018
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Souliotis, Marinos (author)
In the race for cost reduction in the offshore wind industry, support structure optimization leading to weight reduction plays a prominent role. The fatigue limit state is often the driving consideration for support structure design. Monitoring the monopile loads can offer an accurate knowledge of its consumed and remaining fatigue lifetime,...
master thesis 2017
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Goes, Sten (author)
The millions of filter weights in Convolutional Neural Networks (CNNs), all have a well-defined and analytical expression for the partial derivative to the loss function. Therefor these weights can be learned from data with a technique called gradient descent optimization. While the filter weights have a well-defined derivative, the filter size...
master thesis 2017
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Ivanov, Viktor (author)
Model selection is associated to model assessment, which is the problem of comparing different models, or model hyperparameters, for a particular learning task. It constitutes a fundamental step in building machine learning models. The central question is: How a model will work in the future? In this thesis, a new model selection scheme for...
master thesis 2017
document
Warmerdam, Santor (author)
Automated instrument recognition is necessary to efficiently obtain instrumentation information for the existing large collections of digital music. While automated instrument recognition is possible with very high accuracy for monophonic fragments, the problem has not yet been solved for polyphonic mixes.In this work a system is designed for...
master thesis 2017
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Harrison, Joe (author), Dikken, Olivier (author), van Peer, Dennis (author)
FeedbackFruits is a company that provides tools for educators to organize their courses. The company is currently working on aiding teachers in aligning course material and assessment. Aligning the two provides students with clear expectations and can lead to an increase in learning [1]. Aligning course material and assessment is usually done by...
bachelor thesis 2017
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Scherp, L. (author)
Airline maintenance technicians (AMTs) often still rely on paper-based documentation when performing a task. In the limited time during unscheduled tasks, obtaining the right information from these documents can take up to 30% of the available time. To speed up this process, in this thesis it is explored how an automated system can be created...
master thesis 2016
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Regtuit, R.M. (author)
Acceptance of automation has been a bottleneck for successful introduction of automation in Air Traffic Control. Strategic conformal automation has been proven to increase automation acceptance, by creating a better match between automation and operator decision-making. In this paper strategic conformal automation for Air Traffic Control is...
master thesis 2016
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Parolas, I. (author)
The hinterland transportation of incoming containers at container terminals is a complex problem, due to the various actors involved and their often conflicting interests. A promising solution towards the problem for hinterland network operators is that of synchromodality, a concept that refers to on-line network planning for hinterland...
master thesis 2016
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Viering, T.J. (author)
In many settings in practice it is expensive to obtain labeled data while unlabeled data is abundant. This is problematic if one wants to train accurate (supervised) predictive models. The main idea behind active learning is that models can perform better with less labeled data, if the model may choose the data from which it learns. Active...
master thesis 2016
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Santegoeds, O.J. (author)
master thesis 2016
document
Bender, D.W.B. (author)
Modern industrial plants contain enormous numbers of sensors which, in turn, generate enormous amounts of process and diagnostic variable measurements. All this generated data is stored in a Data Historian database and then left untouched. This report evaluates whether there is useful information amongst this unused data, and if so, how this...
master thesis 2016
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Langenkamp, W.H. (author)
Reinforcement learning is a machine learning paradigm that deals with optimisation and learns by interacting with its environment. Tabular reinforcement learning methods are popular because of their relative simplicity combined with good guarantees of finding an optimal solution. The downside is that they suffer from an exponentially growing...
master thesis 2016
document
Gonzalez Godinez, L.A. (author)
Wearable devices have paved way for several context-aware applications in the field of health-care and sports to improve the well-being of users and their performance for human augmentation. During rehabilitation patients need accurate feedback that can empower and improve the speed of recovery. On the other hand competitive athletes need a...
master thesis 2016
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Olij, D.J.C. (author)
In this thesis 6 wave climate reduction methods are described and evaluated. Of these methods, 3 are commonly used in literature and 3 are machine learning methods that are adjusted so that they can be used for the reduction of a wave climate. The evaluation is executed with the use of a Delft3D model of the coast of Durban, South Africa.
master thesis 2015
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Raats, J.M. (author), Van der Zwan, L.F. (author)
The Investment Department of ING asked us to build a model that predicts customer loyalty using the Net Promoter Score (NPS) system and a dashboard that would show the results of the model. With this model and dashboard ING may be able to get an insight into which groups of customers are at risk to complain.
bachelor thesis 2015
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Nugroho, H. (author)
Optical beamforming networks (OBFNs), which consist of many small and flat antennas, called phased array antennas (PAAs), can be tuned such that the signal beam from the airplanes can be steered towards a satellite. This was proposed as a alternative to the mechanically steered antenna, which has many disadvantages. The problem of tuning a large...
master thesis 2015
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