Searched for:
(1 - 20 of 108)

Pages

document
Ritsma, Folkert (author)
Performance of set based fault detection is highly dependent on the complexity of the set bounding methods used to bound the healthy residual set. Existing methods achieve robust performance with complex set bounding that narrowly define healthy system behavior, yet at the cost of higher computation times. In this thesis a major improvement is...
master thesis 2019
document
Herber, Nils (author)
The use of machine learning systems has great potential to better predict probabilities of default for credit underwriting. Despite this advantage, herewith there exists the substantial risk of discrimination. Moreover, machine learning models with the highest prediction-accuracy are often the least explicable (i.e. explainable). Nonetheless,...
master thesis 2019
document
Martini, Giulia (author)
Despite therelevance of the road infrastructure, the mechanisms governing the mechanicalproperties of asphalt concrete pavements, are currently not sufficientlyunderstood. Many empirical models of different complexity are proposed in theliterature; however, (i) they all have below high (R2 =0.85) predictiveaccuracy; (ii)...
master thesis 2019
document
Strafforello, Ombretta (author)
With the huge amount of data that is collected every day and shared on the internet, many recent studies have focused on methods to make multimedia browsing simple and efficient, investigating techniques for automatic multimedia analysis. This work specifically delves into the case of information extraction from videos, which is still an open...
master thesis 2019
document
Wiersma, Ruben (author)
We present a new approach for deep learning on surfaces, combining geometric convolutional networks with rotationally equivariant networks. Existing work either learns rotationally invariant filters, or learns filters in the tangent plane without correctly relating orientations between different tangent planes (orientation ambiguity). We propose...
master thesis 2019
document
Pop, Marius (author)
Security has become ever more important in today's quickly growing digital world as the number of digital assets has quickly grown. Our thesis focuses on devices that compute a secure cryptographic operation such that information can be communicated or authenticated. The attack vector utilized is known as Profiled Side-Channel Analysis (SCA)...
master thesis 2019
document
Blauw, Alexander (author)
Turbulent flows are commonly encountered in scientific research or engineering applications and need simulations to be resolved. The Navier-Stokes equations govern the simulations of turbulent flows. One of the most common ways to solve the Navier-Stokes equations is to analyse the Reynolds averaged form (RANS). Next to the increasing...
master thesis 2019
document
de Bruijn, Janno (author)
In the Netherlands there are many bridges that crosses waterways, which are key nodes in the transportation system. The safety and integrity of these bridges is nowadays assessed by (visual) inspections at regular intervals. This approach cannot provide information about damage development in between inspections, leading to potential failure or...
master thesis 2019
document
Kapadia, Husain (author)
Listening in noise is a challenging problem that affects the hearing capability of not only normal hearing but especially hearing impaired people. Since the last four decades, enhancing the quality and intelligibility of noise corrupted speech by reducing the effect of noise has been addressed using statistical signal processing techniques as...
master thesis 2019
document
Graur, Dan (author)
Given the increasing popularity of Machine Learning, and the ever increasing need to solve larger and more complex learning challenges, it is unsurprising that numerous distributed learning strategies have been brought forward in recent years, along with many large scale Machine Learning frameworks. It is however unclear how well these...
master thesis 2019
document
Bhoraskar, Akshay (author)
This study aims at a possible solution to predict the fuel consumption of heavy duty diesel trucks, particularly, the tractor semitrailer for their long haul operations using various machine learning techniques. It intends to provide a possible alternative to simulation or physics based models, which often are very complicated. The stringent...
master thesis 2019
document
Sirenko, Mikhail (author)
master thesis 2019
document
Gu, Nien-Hua (author)
The thesis addresses the implementation challenges of Machine Learning (ML) for merchandisers in the scenario of digitalization of retailing, and proposes a product-service design as the solution. The digitalization of retailing is defined as an on-going process to integrate Internet-connected digital technologies into interfaces between...
master thesis 2019
document
Noppen, Marko (author)
Adaptive optics are widely used to correct the wavefront distortion imposed by atmospheric turbulence. Focal plane phase retrieval from intensity measurements has advantages due to the ease of implementation, potential broader application, less computations, low cost, high system bandwidth, simplified hardware and less calibration. To cope with...
master thesis 2019
document
Friđriksdóttir, Esther (author)
Physical activity and mobility are important indicators of the recovery process of patients in the general ward of the hospital. Currently, monitoring mobility of hospitalized patients relies largely on direct observation from the caregivers. Accelerometers have the potential to quantify physical activity of patients objectively and without...
master thesis 2019
document
Kras, Etienne (author)
Today's coastal zones are densely inhabited as the majority of the world's population lives in these attractive areas. The shorelines in coastal zones are shaped by complex spatial and temporal variable interactions between natural forcings like changes in mean sea-level, tides, wave and wind conditions, and storm surges. Besides, natural...
master thesis 2019
document
Elghlan, Faris (author)
This M.Sc. thesis report investigates the application of one-class classification techniques to complex high-dimensional data. The aim of a one-class classifier is to separate target data from non-target data, but only a dataset containing target data is available for training. The issue with high-dimensional data is that it is difficult to...
master thesis 2019
document
Reinbergen, Hugo (author)
The analysis of lawfully intercepted traffic is a key part of many investigations of criminal activity. This makes it vitally important that the intercepted data is correct and that issues with the configuration of the network or interception solution do not contain errors. A late discovery of a problem in either the network setup or the traffic...
master thesis 2019
document
van der Valk, Daan (author)
Side-channel attacks (SCA) aim to extract a secret cryptographic key from a device, based on unintended leakage. Profiled attacks are the most powerful SCAs, as they assume the attacker has a perfect copy of the target device under his control. In recent years, machine learning (ML) and deep learning (DL) techniques have became popular as...
master thesis 2019
document
Shriram, Sharad (author)
Modern web information systems use machine learning models to provide personalized user services and experiences. However, machine learning models require annotated data for training, and creating annotated data is done through crowdsourcing tasks. The content used in annotation crowdsourcing tasks like medical records and images might contain...
master thesis 2019
Searched for:
(1 - 20 of 108)

Pages