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Vermeer, Jort (author)The Random Finite Element Method (RFEM) is a robust stochastic method for slope reliability analysis that incorporates the spatial variability of soil properties. However, the extensive computational time associated with the direct Monte Carlo simulation limits its practical application. To overcome this problem, this study investigates the use...master thesis 2024
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Kappé, Jeroen (author)The city of Amsterdam faces the challenge of monitoring and assessing 200 kilometers of historic quay walls, of which much is deemed to be in poor condition. A key monitoring technique used is photogrammetry resulting in deformation testing. The fundamental data source forming the basis of this deformation analysis is a collection of overlapping...master thesis 2024
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Yin, Junzhe (author)The thesis explores an innovative technique for enhancing the precision of short-term weather forecasts, particularly in predicting extreme weather phenomena, which present a notable challenge for existing models such as PySTEPS due to their volatile behavior. Leveraging precipitation and meteorological data sourced from the Royal Netherlands...master thesis 2024
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Graauw, Mitchel (author)The dose computation algorithm, or dose engine, is one of the fundamental parts of radiotherapy treatment planning. These algorithms predict how the dose will be distributed inside the patient.<br/>Current dose engines are mainly based on either Monte Carlo simulations (MC) or pencil beam algorithms (PBA). MC being very precise, but relatively...master thesis 2024
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Roy, Ankush (author)Extreme precipitation, like floods and landslides, poses major risks to safety and the economy, underscoring the need for sophisticated weather forecasting to predict these events accurately, enhancing readiness and resilience. Nowcasting, which uses real-time atmospheric data to predict short-term weather, is key in addressing this challenge....master thesis 2024
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Mertzanis, Nick (author)This thesis investigates the integration of algorithm unrolling and genetic algorithms (GA) for optimizing pump scheduling in water distribution systems (WDS), a critical component for ensuring energy-efficient water delivery. In the context of modern civilization’s reliance on clean, affordable water for diverse uses, the operation of a WDS,...master thesis 2024
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Rijpkema, Gerben (author)Forensic microtrace investigation relies on a time- and labour-intensive process of manually analysing samples via microscopy. To aid forensic experts in their investigations, an image recognition model for microtrace localisation and classification is needed. This work investigates the trace recognition accuracy that can be achieved by...master thesis 2024
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Niemantsverdriet, Ruben (author)The periconceptional period, encompassing the embryonic phase, is a critical window where a majority of reproductive failures, pregnancy complications, and adverse pregnancy outcomes arise. The Carnegie staging system comprises 23 stages which are based on embryonic morphological development. This allows for the assessment of normal and abnormal...master thesis 2024
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Nelemans, Peter (author)Fully distributed hydrological models take into account the spatial variability of a catchment, and allow for assessing its hydrological response at virtually any location. However, these models can be time-consuming when it comes to model runtime and calibration, especially for large-scale catchments. Meanwhile, deep learning models have shown...master thesis 2024
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Doornbos, Marie-Claire (author)Objective: This study introduces a novel deep-learning-based orientation recognition approach for detecting intraoperative lung orientation during robot-assisted anatomical resections, including lobectomy and segmentectomy. This method can potentially aid in anatomical structure identification, facilitate training and education, improve...master thesis 2024
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Qin, Xusen (author)Neural networks have made significant progress in domains like image recognition and natural language processing. However, they encounter the challenge of catastrophic forgetting in continual learning tasks, where they sequentially learn from distinct datasets. Learning a new task can lead to forgetting important information from previous tasks,...master thesis 2024
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Sebus, Siert (author)The Deep Neural Network (DNN) has become a widely popular machine learning architecture thanks to its ability to learn complex behaviors from data. Standard learning strategies for DNNs however rely on the availability of large, labeled datasets. Self-Supervised Learning (SSL) is a style of learning that allows models to also use unlabeled data...master thesis 2024
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van Zwienen, Benjamin (author)In the literature, neural network compression can significantly reduce the number of floating-point operations (FLOPs) of a neural network with limited accuracy loss. At the same time, it is common to manually design smaller networks instead of using modern compression techniques. This thesis will compare the two approaches for the object...master thesis 2023
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Edelman, Jory (author)Magnetic resonance electrical properties tomography is a type of quantitative magnetic resonance imaging that aims to reconstruct the conductivity and permittivity of biological tissue. These electrical properties of the tissue can be used to compute the specific absorption rate, to differentiate tumours from healthy tissue and for hyperthermia...master thesis 2023
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Harte, Jesse (author)In this thesis we aim to research and design different neural models for session recommendation. We investigate the fundamental neural models for session recommendation, namely BERT4Rec, SASRec and GRU4Rec and subsequently use our findings to design a simpler but performant neural model. <br/><br/>Firstly, we address methodological errors made...master thesis 2023
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Solà Roca, Albert (author)Water distribution networks (WDNs) provide drinking water to urban and rural consumers through a network of pipes that transport water from reservoirs to junctions. Water utilities rely on tools such as EPANET to simulate and analyse the performance of water distribution networks (WDNs). EPANET solves the flow continuity and headloss equations...master thesis 2023
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Bagchi, Madhubanti (author)Recently non-image-based data capturing methods such as sensors like RF, ultrasonic or radars, Wi-Fi, Bluetooth, etc for People Counting (PC) applications have gained momentum as an alternative to camera-based systems due to the preference for privacy preservation. Among them mm-wave radars are a strong choice for data capture since they consume...master thesis 2023
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Zou, Yanghuan (author)Machine learning models offer promising potential in precipitation nowcasting. However, a common issue faced by many of these models is the tendency to produce blurry precipitation nowcasts, which are unrealistic. Previous research on the deep learning model - TrajGRU (Shi et al., 2017) indicated that data imbalance in radar images and the...master thesis 2023
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Jiang, Haitao (author)The technique of ultrasound-guided needle insertion is commonly employed in various clinical fields, including biopsy, anesthesia, brachytherapy, and ablation. However, the visibility of the needle in ultrasound (US) images remains a persistent challenge. To improve the guidance accuracy of needle insertion during interventions, it is crucial to...master thesis 2023
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Giraud, Bastien (author)The transition to green energy is reshaping the energy landscape, marked by increased integration of renewable energy sources, distributed resources, and the electrification of other energy sectors. These changes challenge grid security, particularly regarding the N-1 security criterion, a crucial factor in preventing blackouts. Furthermore,...master thesis 2023