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Li, Sitong (author), Rao, Chengzhi (author), Zhang, Chi (author), Wei, Wei (author)
In a rapidly evolving digital landscape, 3D city models have become more accurate and complex. Despite their widespread availability of open-source 3D city model datasets, these invaluable resources remain underutilized. Our primary goal centers on the classification of building and roof types. For our client, Spotr, our work directly impacts on...
student report 2023
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Heidekamp, Mathijs (author)
Resistive random access memory (RRAM) is an emerging memory technology that has the potential to replace dynamic random access memory (DRAM) or FLASH. The current memory technology suffer from scalability issues. RRAM can be used as potential replacement for Flash and DRAM. RRAM stores information using resistance states instead of charge. RRAM...
master thesis 2023
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Li, David (author)
Technological devices are ubiquitous, think of for example smartphones and in-vehicle information systems. Both can contribute towards distracted driving where the visual field of the human controller is shifted away from the primary control task. In this paper a neural network model is trained using the InceptionTime architecture and used to...
master thesis 2023
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Mansour Pour, K. (author)
Borehole operations play a crucial role in managing various subsurface activities related to energy, including energy storage, geothermal energy production, CO2 sequestration, oil and gas extraction, wastewater disposal, and thermal recovery processes. In recent times, intelligent well technologies, such as long deviated multi-lateral wells...
doctoral thesis 2023
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Gnanavarothayan, Kabilan (author)
The use of Internet of Things (IoT) devices has experienced an increase since its inception and is expected to continue to do so. However, this growth has also attracted individuals with malicious intentions. Botnet attacks on IoT devices have become more potent each year, exploiting new vulnerabilities and attacking more devices. Therefore, it...
master thesis 2023
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Rang, Jugo (author)
This paper presents a novel approach for the estimation of conditional multivariate cumulative distribution functions (CDFs) within a nonparametric framework. To achieve this, we introduce a binary random variable that indirectly represents conditional CDFs and construct a dataset by pairing input vectors with the binary variables. We developed...
master thesis 2023
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Wigmans, Bram (author)
This paper examines whether complex high-dimensional data that describes the dynamics of a cantilever beam can be transformed into a less complex system. In particular, the transformation that is examined is the reduction of the dimension. An essential aspect of this study involves the implementation of a linear autoencoder, which is a type of...
bachelor thesis 2023
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Smeenk, Rutger (author)
This research aims at quantifying the uncertainty in the predictions of tensor network constrained kernel machines, focusing on the Canonical Polyadic Decomposition (CPD) constrained kernel machine. Constraining the parameters in the kernel machine optimization problem to be a CPD results in a linear computational complexity in the number of...
master thesis 2023
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Balayn, A.M.A. (author)
Machine learning (ML) is an artificial intelligence technology that has a great potential for being adopted in various sectors of activities. Yet, it is now also increasingly recognized as a hazardous technology. Failures in the outputs of an ML system might cause physical or social harms. Besides, the development and deployment of an ML system...
doctoral thesis 2023
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Nijsse, Paul (author)
Myeloproliferative Neoplasms (MPNs) are a group of bone marrow diseases with potentially lethal cardio-vascular complications. Two sub-diseases of MPN are Essential Thrombocytosis (ET) and Polycythemia Vera (PV), which are recognised by an abnormal blood count of respectively thrombocytes and red blood cells.<br/><br/>If an MPN is treated...
master thesis 2023
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VASILEIOU, ANTONIOS (author)
Graph data is widely used in various applications, driving the rapid development of graph-based machine learning methods. However, traditional algorithms tailored for graphs have constraints in capturing intricate node relationships and higher-order patterns. Recent insights from prior research have shed light on comparing different graph neural...
master thesis 2023
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Schmidt, Stephan (author)
This paper examines the end-to-end development process for a Convolution Neural Network (CNN) based damage classification tool for ultrasonic inspection of aerospace-grade composite structures. The recent advent of Artificial Intelligence (AI) and Machine Learning (ML) has piqued the interest of the aerospace industry since it has the potential...
master thesis 2023
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Patalay, Prathamesh (author)
PROBLEM<br/>Foundation Models are emerging as a new paradigm in AI research &amp;<br/>commercialisation. While this opens up possibilities for radically innovative<br/>solutions and significant value creation, startups are challenged with finding<br/>unique &amp; differentiated ways to leverage the technology, while simultaneously<br/>mitigating...
master thesis 2023
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van Spengler, Olivier (author)
Demand forecasting plays a critical role in organizational planning, encompassing inventory management, capacity allocation, and financial decision-making. However, achieving accurate forecasts can be challenging, particularly in industries characterized by high demand volatility, such as semiconductor assembly equipment manufacturing,...
master thesis 2023
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Lu, Guang (author)
This research project delves into the exploration of the sound environment within Intensive Care Units (ICUs), particularly focusing on Neonatal Intensive Care Unit (NICU) and Pediatric Intensive Care Unit (PICU). It aims to enhance the understanding of sound events and their impact on both nurses' decision-making and patients' sleep behaviors....
master thesis 2023
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Kyriazis, Ioannis (author)
Patients with neuromuscular diseases that are unable to speak, but whose cognitive ability has been maintained, can be benefited from Brain Computer Interfaces (BCIs). The decoding of inner (covert) speech from EEGs consists of one of the state of the art methods that aim to tackle this issue. High variability between subjects, as well as low...
master thesis 2023
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Vos, Gerard (author)
The political interest in fish habitat suitability and, consequently, of fish populations has increased. The fish habitat suitability is a key factor for successful ecological restoration, for example via dam removal and implementation of fish passage. Furthermore, the fish population composition determines the ecological quality of water bodies...
master thesis 2023
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Frassini, Emanuele (author)
In our research, we have made a significant advancement in predicting the clinical outcome of high-risk non-muscle invasive bladder cancer (HR-NMIBC) by combining clinicopathological data with image-related features. This integrated approach has shown remarkable improvements in the accuracy of artificial intelligence techniques for outcome...
master thesis 2023
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Holtgrefe, Tim (author)
Microtubules are long cylindrical polymers, assembled from tubulin proteins. Microtubule ends can be visualized using fluorescence and confocal microscopy. This allows for the study of microtubule dynamics. However, the manual annotation of microtubules is laborious, which is why automated tracking methods are used. In this project we have...
bachelor thesis 2023
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Bhat, Ullas (author)
The use of small satellites, enabled by the standardization of the CubeSat specifications and miniaturization in electronics, has seen a rapid increase in the past decades. The low-cost and short development time of these satellites has made them an attractive option for both commercial and academic applications, making space exploration more...
master thesis 2023
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