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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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Lee, Y. (author)E-learning has shifted the traditional learning paradigms in higher education, offering more flexible, ubiquitous, and personalized learning experiences. The previous years COVID-19 pandemic required a re-calibration of education to accommodate virtual learning environments from the traditional classroom-based education. Widespread learning...doctoral thesis 2024
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Lu, C.J. (author)Real-time nonintrusive occupancy estimation can maximize the use of existing sensors to infer occupant information in buildings with the advantages of fewer privacy concerns and fewer extra device costs. Recently, many deep learning architectures have proven effective in estimating occupancy directly from raw sensor data. However, some...journal article 2024
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Martinez Lopez, V.A. (author), van Urk, G.A. (author), Doodkorte, P.J.F. (author), Zeman, M. (author), Isabella, O. (author), Ziar, H. (author)Clouds moving in front or away from the sun are the leading cause of irradiance variability. These variations have a repercussion on the electricity production of photovoltaic systems. Predicting such changes is essential for proper control of these systems and for maintaining grid stability. Images from the sky have proven to help with short...journal article 2024
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van Nuland, T.D.H. (author)The universal approximation theorem is generalised to uniform convergence on the (noncompact) input space R<sup>n</sup>. All continuous functions that vanish at infinity can be uniformly approximated by neural networks with one hidden layer, for all activation functions φ that are continuous, nonpolynomial, and asymptotically polynomial at ±∞...journal article 2024
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Wang, X. (author), Corzo, Gerald (author), Lü, Haishen (author), Zhou, Shiliang (author), Mao, K. (author), Zhu, Yonghua (author), Duarte Prieto, F.S. (author), Liu, Mingwen (author), Su, Jianbin (author)Sub-seasonal drought forecasting is crucial for early warning in estimating agricultural production and optimizing irrigation management, as forecasting skills are relatively weak during this period. Soil moisture exhibits stronger persistence compared to other climate system quantities, which makes it especially influential in shaping land...journal article 2024
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Zhang, Xiang (author), Touya, Guillaume (author), Meijers, B.M. (author)Automated map generalization has been a major area of research for decades but has still not reached maturity. Besides the needs for more adaptive algorithms, a fundamental question remains: How can we transfer human generalization knowledge into a computational system more effectively? Previous efforts do not seem capable to fully overcome the ...contribution to periodical 2024
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Kashifi, M.T.K. (author)Road traffic crash is a global tragedy that leads to economic loss, injury, and fatalities. Understanding the severity of a road crash at the early stages is vital to timely providing emergency medical services to crash victims. This study developed a crash emergency response management framework that requires basic crash information for...journal article 2024
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Martin, H.A. (author), Xu, Haojia (author), Smits, Edsger C.P. (author), van Driel, W.D. (author), Zhang, Kouchi (author)This study introduces a training protocol utilizing Convolutional Neural Networks (CNNs) and Confocal Scanning Acoustic Microscopy (CSAM) imaging techniques to classify Power Quad Flat No-leads (PQFN) package delamination. The investigation involves empty PQFN packages with varied substrate metallizations subjected to thermal cycling. Four...conference paper 2024
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Paredes-Vallés, Federico (author)In the ever-evolving landscape of robotics, the quest for advanced synthetic machines that seamlessly integrate with human lives and society becomes increasingly paramount. At the heart of this pursuit lies the intrinsic need for these machines to perceive, understand, and navigate their surroundings autonomously. Among the senses, vision...doctoral 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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Masouris, Thanos (author)Chess recognition refers to the task of identifying the chess pieces configuration from a chessboard image. Contrary to the predominant approach that aims to solve this task through the pipeline of chessboard detection, square localization, and piece classification, we rely on the power of deep learning models and introduce two novel...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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Schuurman, Kevin (author)The use of deep learning in global weather forecasting has shown significant promise in improving both forecasting accuracy and speed. Traditional numerical weather prediction models have gradually improved forecasting skills but at the cost of increased computational complexity. In contrast, new deep learning models, trained directly on...master thesis 2023
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Geel, Patrick (author)The demand for implementing neural networks on edge devices has rapidly increased as they allow designers to move away from expensive server-grade hardware. However, due to the limited resources available on edge devices, it is challenging to implement complex neural networks. This study selected the Kria SoM KV260 hardware platform due to its...master thesis 2023
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Tebbens, Ricardo (author)There is a raising demand for player statistics in the world of football. With the developments over the last years in wearable sensors, Human Activity Recognition (HAR) based on wearable IMU sensors can be used to tackle this problem. This thesis builds upon an earlier research done for this topic, where an end-to-end pipeline based on deep...master thesis 2023
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do Lago, Cesar A.F. (author), Giacomoni, Marcio H. (author), Bentivoglio, Roberto (author), Taormina, R. (author), Gomes, Marcus N. (author), Mendiondo, Eduardo M. (author)Two-dimensional hydrodynamic models are computationally expensive. This drawback can limit their application to solving problems requiring real-time predictions or several simulation runs. Although the literature presented improvements in using Deep Learning as an alternative to hydrodynamic models, Artificial Neural Networks applications for...journal article 2023
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MENG, YUQI (author)Traditionally, archaeological investigations, especially archaeological remains detection, mostly depend on human observation. In order to find the objects in large areas, a lot of fieldwork has to be done and it takes a long time for archaeologists to travel around. Nowadays, the development of LIDAR provides accurate 3D geometric information,...master thesis 2023
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Mink, Raoul (author)Decentralised drone swarms need real time collision avoidance, thus requiring efficient, real time relative localisation. This paper explores different data inputs for vision based relative localisation. It introduces a novel dataset generated in <i>Blender</i>, providing ground truth optic flow and depth. Comparisons to <i>MPI Sintel</i>, an...master thesis 2023
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Rahmani, S. (author), Baghbani, Asiye (author), Bouguila, Nizar (author), Patterson, Zachary (author)Graph neural networks (GNNs) have been extensively used in a wide variety of domains in recent years. Owing to their power in analyzing graph-structured data, they have become broadly popular in intelligent transportation systems (ITS) applications as well. Despite their widespread applications in different transportation domains, there is no...journal article 2023