Searched for: subject:"Machine%5C+Learning"
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Verburg, Floris (author)
For performing technical maintenance, it is important to keep a detailed schedule of resources and temporal constraints. The Resource Constrained Project Scheduling Problem (RCPSP) is a well de- fined scheduling model with both resources and temporal constraints. Precedence Constraint Posting (PCP) is a technique to solve the NP-hard RCPSP...
master thesis 2018
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Kouw, W.M. (author)
Artificial intelligence, and in particular machine learning, is concerned with teaching computer systems to perform tasks. Tasks such as autonomous driving, recognizing tumors in medical images, or detecting suspicious packages in airports. Such systems learn by observing examples, i.e. data, and forming a mathematical description of what types...
doctoral thesis 2018
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Ruiz Arenas, S. (author)
Typically, emerging system failures have a strong impact on the performance of industrial systems as well as on the efficiency of their operational and servicing processes. Being aware of these, maintenance and repair researchers have developed multiple failure detection and diagnosis techniques that allow early recognition of system or...
doctoral thesis 2018
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Wymenga, Jan (author)
This work presents a multi-sensor approach for weather condition estimation in automated vehicles. Using combined data from weather sensors (barometer, hygrometer, etc) and an in-vehicle camera, a machine learning and computer vision framework is employed to estimate the current weather condition in realtime and in-vehicle. The use of different...
master thesis 2018
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van Marrewijk, Gijsbert (author)
Launch costs for high-resolution space telescopes for Earth observation can be reduced when the telescope mirrors are made deployable. However, such a system is subject to optical aberrations that decreases image quality. To counter these aberrations, an Aberration Correction System (ACS) is proposed that uses a deformable mirror (DM) which is...
master thesis 2018
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den Hartog, Daniel (author)
Self-driving vehicles are the future of automotive engineering. Systems that take over control from the driver are developed to be able to interact with the conditions of the road and other obstacles. To develop these systems, developers use vehicle models to simulate the behaviour of the moving vehicle. The systems developed using these models...
master thesis 2018
document
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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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
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Uijens, Wouter (author)
Convolutional Neural Networks (CNNs) are achieving state of the art performance in computer vision. One downside of CNNs is their computational complexity. One way to make CNNs more computational efficient is by implementing their convolutions in the frequency domain, using Fast Fourier Transforms (FFTs). This has as a consequence that most...
master thesis 2018
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Döpke, Max (author)
In this research a global-coefficient non-linear eddy viscosity model (NLEVM) is studied. This model stems from the inherent inability of the Boussinesq approximation to model anisotropy and therefore flow features such as: swirl, stream-line curvature and secondary motions (Lumley, 1970; Pope, 1975; Craft et al., 1996). The focus lies on the...
master thesis 2018
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van der Arend, Dennis (author)
Traditionally a wind turbine’s power curve is used to model the long-term energy yield of the wind turbine and afterwards assess the performance of the turbine (power curve verification). But the current power curve is typically univariate: only dependent on the wind speed and slightly adjusted for site density, turbulence intensity and wind...
master thesis 2018
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Dai, Lu (author)
Planning and scheduling problem is a hard problem, especially in real life cases. The time and space complexity increase quickly along with the increase of problem size. In transportation systems, such problems exist a lot. The automation of transportation systems depends a lot on the improvements of developing planning and scheduling algorithm....
master thesis 2018
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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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Tajalizadehkhoob, S. (author)
In theory, hosting providers can play an important role in fighting cybercrime and misuse. This is because many online threats, be they high-profile or mundane, use online storage infrastructure maintained by hosting providers at the core of their criminal operations.
However, in practice, we see large differences in the security measures...
doctoral thesis 2018
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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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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
Searched for: subject:"Machine%5C+Learning"
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