Searched for: subject:"machine%5C+learning"
(1 - 20 of 69)

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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
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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
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Sahla, Nordin (author)
The last decade has marked a rapid and significant growth of the global market of warehouse automation. The biggest challenge lies in the identification and handling of foreign objects. The aim of this research is to investigate whether a usable relation exist between object features such as size or shape, and barcode location, that can be used...
master thesis 2018
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Dukai, Balázs (author)
There are several 3D city models available openly, worldwide. These models are used in various applications, from which many expects a homogeneous Level of Detail (LoD). Validating the accuracy of the LoD of a model requires the inference its LoD class and its conformance to the real-world object. This process quickly becomes infeasible for...
master thesis 2018
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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
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Andriessen, Frerik (author)
Space exploration could be significantly aided by combining the disciplines of machine learning and computer vision, but these disciplines need to be developed further for specific space-related applications to have merit. One of the applications for space exploration is the detection of certain structures designating areas of interest. This...
master thesis 2018
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Humala, Bontor (author)
Providing detailed appliance-level energy consumption information helps consumers to understand their usage behavior and encourages them to optimize their energy usage. Non-intrusive load monitoring (NILM) or energy disaggregation aims to estimate appliance-level energy consumption data from the aggregate consumption data of households. NILM...
master thesis 2018
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Gulden, Freek (author)
Decision- and policymakers responsible for the coastal zone aim at combining measures against for instance long-term erosion, with measures that have a positive social, economic impact on the region. Recreational beach usage has a large social economic impact on a region and therefore quantification of the recreational beach usage can provide...
master thesis 2018
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Capelle, Lotte (author)
This thesis describes three different predictive frameworks which are applied to improve the interaction behavior between a robot and their users. Machine learning is used to train the frameworks. The training data contains information obtained from one user over a period of approximately 3 to 30 days. This work is applied to the LEA robot: an...
master thesis 2018
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de Groot, Olivier (author)
Free competition in the insurance markets increases the competitiveness and lowers the premiums. If insurers lower their premiums without having a model that accurately quantifies the expected claim size, they can be in serious trouble. This research aims to accurately model the premiums and quantify the uncertainty involved using historic...
master thesis 2017
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Carzana, Livio (author)
When sunlight illuminates a body, a tiny pressure is exerted upon its surface due to the photons impacting on it. Such a principle forms the basis of solar sailing, in which the solar radiation pressure is used to accelerate highly reflective lightweight structures called solar sails. Similarly, a laser-enhanced solar sail is a solar sail in...
master thesis 2017
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Vermeer, Kaz (author)
Advanced tools such as machine learning are slowly finding their way into the modern scientist’s toolbox . In the design of mechanical systems however hardly any machine learning applications are being used. Research into the viability of such an application is therefore necessary.
We have performed such research, using a specific type of...
master thesis 2017
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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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Aslam, Muhammad Najeeb (author)
master thesis 2017
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Echaniz Soldevila, Ignasi (author)
This master thesis aims to gain new empirical insights into longitudinal driving behavior by means of the enumeration of a new hybrid car-following (CF) model which combines parametric and non parametric formulation. On one hand, the model, which predicts the drivers acceleration given a set of variables, benefits from innovative machine...
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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Liscio, Enrico (author)
Autonomous grasping is a key requisite for the autonomy of robots.
However, grasping of unknown objects in domestic environments is difficult due to the presence of unpredictability and clutter.
In this paper, a novel algorithm capable of finding an unobstructed grasping pose on unknown regular object shapes in cluttered environments is...
master thesis 2017
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Yan, Yuzhu (author)
Analyzing large cryptographic protocol implementations can be challenging since their implementations do not perfectly match the standard [6]. The popular, highly configurable remote login method, Secure Shell (SSH) is such an example. In this thesis, we researched the fuzzing methodologies for SSH implementations. Three tools (Backfuzz,...
master thesis 2017
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Choiri, Hendra Hadhil (author)
Analysing attractiveness of places in a region is beneficial to support urban planning and policy making. However, the attractiveness of a place is a subjective and high-level concept which is difficult to quantify. The existing methods rely on traditional surveys which may require high cost and have low scalability. This thesis attempts to...
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
Searched for: subject:"machine%5C+learning"
(1 - 20 of 69)

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