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van Heukelum, Robin (author), Oolbekkink, Gerben (author), Wolting, Matthijs (author)
For traditional, manual real estate appraisals, the appraiser is required to provide a number of comparable properties (the 'Comps'). These comps act as a benchmark for the valuation as well as a provider of context in the final appraisal report. Traditionally, these comps are selected manually by an appraiser based on recent transactions within...
bachelor thesis 2018
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Katzy, Jonathan (author), Rietveld, Tim (author), van der Steeg, Jaap-Jan (author), Wiegel, Erik (author)
As Machine Learning is becoming more accessible to small businesses, thanks to the rapid advance in computing power, smaller start-ups such as Sjauf (a ride sharing start-up) are starting to get interested in implementing Machine Learning solutions in their product. Sjauf needed a system that could automatically tell its customers how much a...
bachelor thesis 2018
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Safarpour Erfani, Ramin (author), Bilstra, Cas (author), Koppers, Shane (author), List, Floris (author)
Omnicom Media Group (OMG) is a company heavily involved in marketing and advertising. Our client is Annalect, a solutions provider that helps the marketers of OMG to make data actionable. OMG has processed cookie data to help their marketers set up advertisement campaigns. They buy this cookie data from a 3rd party. They also manage, however, a...
bachelor thesis 2017
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Harting, Tom (author), Popping, Sven (author), Post, Mathieu (author), Swaab, Daniël (author)
Being a bank, bunq deals with transaction fraud on a regular basis. All transactions that are handled by bunq are monitored for these cases of fraud by a transaction monitoring system. When this system flags a transaction as being possibly fraudulent, a bunq employee has to manually check this transaction. The problem with the current system is...
bachelor thesis 2017
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Boellaard, B. (author), Bolier, W. (author), Mairet, V. (author), Peeters, T. (author)
This Bachelor Thesis is part of the Bachelor Computer Science and Engineering program at Delft University of Technology. During this project the team had to create an extension to an existing game framework. This extension consisted of improved artificial intelligence for the antagonist and a maze generator that could be re-used as a library....
bachelor thesis 2015
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Wiersma, Ruben (author), Nguyen, Hung (author), Geenen, Alexander (author)
As GeoPhy is developing its business model and looking into the future of automated valu- ation models (AVM), this project delivers a proof of concept of a system that automates the training, maintaining, and delivery of machine learning models for automated valuations. In order to achieve this goal, the situation and problem were first analysed...
bachelor thesis 2017
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Andringa, Sytze (author), Zoon, Job (author), van der Werf, Daan (author)
One of the greatest challenges in marketing is measuring the return of investment of a marketing campaign and translating that into a strategy. Companies spend a lot of money on marketing without knowing how eective certain marketing campaigns are. To solve this problem for bunq, we will be using machine learning to create a marketing...
bachelor thesis 2018
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Kolenbrander, Thomas (author), van Oort, Bart (author), de Ruiter, Frank (author), Yue, Tim (author)
This report describes the process of the Bachelorproject(TI3806) done for ‘De Energiebespaarders’, a startup in Amsterdam striving to make homes more energy efficient through accessible advice and installation of insulation or solar panels. The goal of the project was to apply machine learning to improve their system for identifying house...
bachelor thesis 2017
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Kostense, Bastijn (author), Hageman, Rico (author), van der Wilk, Hilco (author), van Walraven, Bram (author)
For the past 10 weeks, we have been tasked with improving the performance of the transaction monitoring system of bunq, an internationally active mobile bank. bunq has requested that we improve this system by automating the training of the machine learning model, providing better input data for this model and creating additional machine learning...
bachelor thesis 2019
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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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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
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Hugtenburg, Stefan (author)
Wireless sensor networks are commonly used to remotely and automatically monitor environments.<br/>One of the main challenges in wireless sensor networks is to use the limited available energy as efficiently as possible, to ensure longevity of the network. For such networks to survive their intended deployment period no energy may be wasted on...
master thesis 2017
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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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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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Dhar, Aniket (author)
Convolutional neural networks are showing incredible performance in image classification, segmentation, object detection and other computer vision applications in recent years. But they lack understanding of affine transformations to input data. In this work, we introduce rotational invariant<br/>convolutional neural networks that learn...
master thesis 2018
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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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Balayn, Agathe (author)
Training machine learning (ML) models for natural language processing usually requires lots of data that is often acquired through crowdsourcing. In crowdsourcing, crowd workers annotate data samples according to one or more properties, such as the sentiment of a sentence, the violence of a video segment, the aesthetics of an image, ... To...
master thesis 2018
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Garbacz, Mateusz (author)
Being capable to foresee the future of a given financial asset as an investor, may lead to significant economic profits. Therefore, stock market prediction is a field that has been extensively developed by numerous researchers and companies. Recently, however, a new branch of financial assets has emerged, namely cryptocurrencies. As a...
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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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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