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Müller, Lisa-Marie (author)
Across the world, countries are facing housing shortages and the Netherlands is no different. The increasing demand for new housing exceeds the growth rate of the architecture, engineering, and construction industry. Current solutions remain small in scale and therefore unsustainable. Multi-family housing is the optimal typology to address the...
master thesis 2023
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Bruggink, Daan (author)
Traversability estimation is a key component in autonomous driving tasks. In many applications, semantic segmentation is used to pixel-wise classify a visual scene. The pixel-wise segmented map is used to estimate the traversability of different environments. The semantic segmentation accuracy can drop if environmental conditions change. The...
master thesis 2023
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POLYA RAMESH, CHINMAY (author)
Camera-based patient monitoring is undergoing rapid adoption in the healthcare sector with the recent COVID-19 pandemic acting as a catalyst. It offers round-the-clock monitoring of patients in clinical units (e.g. ICUs, ORs), or at their homes through installed cameras, enabling timely, pre-emptive care. These are powered by Computer Vision...
master thesis 2022
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Wang, Zhiyi (author)
Deep-learning models are commonly used in short-term precipitation forecasting. However, most deep-learning models are likely to produce blurry output problems. In order to get realistic and accurate results, AENN, a variant of Generative Adversarial Networks (GANs), has been developed. The AENN implements an additional temporal discriminator to...
master thesis 2022
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Jin, Shuyue (author)
The problem we want to address<br/>AI(Artificial intelligence) is diving into people’s lives as its algorithm continues to iterate. However, the algorithmic and quantitative systems do not seem to access people’s experiences, which always include emotional and qualitative factors. How can an AI system understand people’s feelings? How can an AI...
master thesis 2022
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Brouwer, Hans (author)
Synthesizing audio-reactive videos to accompany music is challenging multi-domain task that requires both a visual synthesis skill-set and an understanding of musical information extraction. In recent years a new flexible class of visual synthesis methods has gained popularity: generative adversarial networks. These deep neural networks can be...
master thesis 2022
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van Oudenhoven, Vincent (author)
An empirical study is performed exploring the sensitivity to hidden confounders of GANITE, a method for Individualized Treatment Effect (ITE) estimation. Most real world datasets do not measure all confounders and thus it is important to know how crucial this is in order to obtain comparable predictions. This is explored through the removal of...
bachelor thesis 2022
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Jehee, Wouter (author)
Federated learning (FL), although a major privacy improvement over centralized learning, is still vulnerable to privacy leaks. The research presented in this paper provides an analysis of the threats to FL Generative Adversarial Networks. Furthermore, an implementation is provided to better protect the data of the participants with Trusted...
bachelor thesis 2022
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Gao, Zhi (author)
Under the increasing electrification of end uses in the energy transition towards more renewable integration, the electricity price keeps gaining importance on every scale from individual well-being to the competitiveness of an economy. Though scarce in the scientific literature, Long-Term Electricity Price Projection (LEPP) has great potentials...
master thesis 2022
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Singh, Akash (author)
Single-cell multi-modal omics promises to open new doors in bioinformatics by measuring different aspects of cells, thus offering multiple perspectives on the underlying biological phenomenon. Although simultaneous multi-modal measurement protocols do exist, their inherent technical limitations necessitate focus on single modality measurements....
master thesis 2021
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Saxena, Mudit (author)
As of 2021, the world economic forum deems cyber-security failures as one of the most potent threats to the world. According to a McAfee report, the cost of cybercrimes in 2020 reached nearly 1 trillion US dollars, which was around 50 percent more than what it was in 2018. Exacerbating the already mammoth financial implication of such a failure...
master thesis 2021
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Kunar, Aditya (author)
While data sharing is crucial for knowledge development, privacy concerns and strict regulation (e.g., European General Data Protection Regulation (GDPR)) unfortunately limit its full effectiveness. Synthetic tabular data emerges as an alternative to enable data sharing while fulfilling regulatory and privacy constraints. The state-of-the-art...
master thesis 2021
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Plesner, M.K. (author)
The key to producing high-fidelity time-series data is to preserve temporal dynamics. This means that generated sequences respect the relationship between variables across time as in the original data. While new types of GANs have been used to generate time-series data, they, like previous GAN<br/>implementations, are time consuming to train. A...
bachelor thesis 2021
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van Rhijn, J. (author)
Generative adversarial networks (GANs) have shown promising results when applied on partial differential equations and financial time series generation. This thesis investigates if GANs can be used to provide a strong approximation to the solution of stochastic differential equations (SDEs) of the Ito type. Standard GANs are only able to...
master thesis 2020
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El Haji, Khalid (author), Posner, Noah (author), Ilbaş, Hakan (author), Karpuz, Sergen (author), Wernet, Victor (author)
As the population increases so does the waste that is generated. Manually recycling waste is expensive and slow. Computer Vision (CV) solutions aim to make this less expensive and faster. Lots of data of this waste (thousands of images) is needed to train these CV solutions. This project, called Synthetic Waste Generator (SWaG) can create...
bachelor thesis 2020
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De Meer Pardo, Fernando (author)
The scarcity of historical financial data has been a huge hindrance for the development algorithmic trading models ever since the first models were devised. Most financial models assume as hypothesis a series of characteristics regarding the nature of financial time series and seek extracting information about the state of the market through...
master thesis 2019
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Uittenbogaard, Ries (author)
In this thesis, a pipeline is created consisting of two parts. In the first part, the moving objects (cars, cyclists, pedestrians) are detected in street-view imagery using image segmentation neural networks and a LIDAR-based moving object detection approach. In the second part, those moving objects are deleted from the image data and an image...
master thesis 2018
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Maton, Max (author)
Creating big datasets is often difficult or expensive which causes people to augment their dataset with rendered images. This often fails to significantly improve accuracy due to a difference in distribution between real and rendered datasets. This paper shows that the gap between synthetic and real-world image distributions can be closed by...
bachelor thesis 2018
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Li, Yadong (author)
Generative adversarial networks (GANs) are a class of generative models, for which the goal is to learn from training data and then to generate data with similar characteristics. Despite the wide use of GANs, a quantitative evaluation method of their performance is lacking. In the current work, we invented a series of artificial datasets,...
master thesis 2018
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