Searched for: subject%3A%22convolution%22
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van Noppen, Thirza (author)
Second-order Gaussian kernels have been utilized to develop three algorithms that could automatically extract ridge lines for hydrodynamic modelling. Isotropic second-order Gaussian kernels produce inaccurate lines at crossings and junctions. To avoid the malfunctioning of Second-order Gaussian kernels, one default and two alternative algorithms...
master thesis 2022
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Norder, Lucas (author)
Conventional Topology Optimization (TO) enables the inverse design of nanophotonic structures by specifying the objective and constraints without a predefined topological concept. Yet, extreme scenarios such as the design of a...
master thesis 2022
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Eijgenraam, Bram (author)
How to deal with the presence of weather affected data is an unavoidable topic in the processing of optical imagery. Clouds and cloud shadows significantly alter the spectral signatures obtained from satellite data, which often leads to problems for any kind of scientific analysis. In this research there has been elaborated on two different kind...
master thesis 2022
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Hashmi, Irtaza (author)
Earthquakes are one of the most dangerous natural disasters that occur worldwide. Predicting them is one of the unsolved problems in the field of science. In the past decade, there has been an increase in seismic monitoring stations worldwide, which has allowed us to design and implement data-driven and deep learning solutions. In this paper, we...
bachelor thesis 2022
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Tran, Tommy (author)
Semantic segmentation methods have been developed and applied to single images for object segmentation. However, for robotic applications such as high-speed agile Micro Air Vehicles (MAVs) in Autonomous Drone Racing (ADR), it is more interesting to consider temporal information as video sequences are correlated over time. In this work, we...
master thesis 2022
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Treurniet, Wiljo (author)
To achieve the goals on greenhouse gas emissions, the energy supply and demand is in transition. Distribution power grids therefore are increasingly reaching their capacity limits due to electrification and the vast increase of distributed energy resource (DER) connection requests with large peak power output. Increasing physical grid capacity...
master thesis 2022
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Kloosterman, Luc (author)
In the future, Air Traffic Controllers are expected to work together with more advanced computer-based automation that can automatically take action. The main challenge is then how to design computer-based tools such that they foster acceptance among air traffic controllers. One possible approach to foster acceptance is by matching the automated...
master thesis 2022
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Dong, Y. (author), Patil, Sandeep (author), Farah, H. (author), van Arem, B. (author)
Reliable and accurate lane detection is of vital importance for the safe performance of Lane Keeping Assistance and Lane Departure Warning systems. However, under certain challenging peculiar circumstances (e.g., marking degradation, serious vehicle occlusion), it is quite difficult to get satisfactory performance in accurately detecting the...
poster 2022
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Eichinger, Matthias (author), Heinlein, A. (author), Klawonn, Axel (author)
A convolution neural network (CNN)-based approach for the construction of reduced order surrogate models for computational fluid dynamics (CFD) simulations is introduced; it is inspired by the approach of Guo, Li, and Iori [X. Guo, W. Li, and F. Iorio, Convolutional neural networks for steady flow approximation, in Proceedings of the 22nd ACM...
journal article 2022
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Vatandaslar, Can (author), Narin, O.G. (author), Abdikan, Saygin (author)
Key message: Despite showing a cost-effective potential for quantifying vertical forest structure, the GEDI and ICESat-2 satellite LiDAR missions fall short of the data accuracy standards required by tree- and stand-level forest inventories. Abstract: Tree and stand heights are key inventory variables in forestry, but measuring them manually...
journal article 2022
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Moradi, M. (author), Ghorbani, R. (author), Sfarra, Stefano (author), Tax, D.M.J. (author), Zarouchas, D. (author)
Assessment of cultural heritage assets is now extremely important all around the world. Non-destructive inspection is essential for preserving the integrity of the artworks while avoiding the loss of any precious materials that make it up. The use of Infrared Thermography (IRT) is an interesting concept since surface and subsurface faults can be...
conference paper 2022
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Yin, Hang (author), Zheng, Feifei (author), Duan, Huan-Feng (author), Savić, Dragan (author), Kapelan, Z. (author)
Urban flooding is a major issue worldwide, causing huge economic losses and serious threats to public safety. One promising way to mitigate its impacts is to develop a real-time flood risk management system; however, building such a system is often challenging due to the lack of high spatiotemporal rainfall data. While some approaches (i.e.,...
journal article 2022
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Chen, Zhijun (author), Lu, Zhe (author), Chen, Qiushi (author), Zhong, Hongliang (author), Zhang, Yishi (author), Xue, J. (author), Wu, Chaozhong (author)
Short-term traffic flow prediction is a core branch of intelligent traffic systems (ITS) and plays an important role in traffic management. The graph convolution network (GCN) is widely used in traffic prediction models to efficiently handle the graphical structural data of road networks. However, the influence weights among different road...
journal article 2022
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Yang, Fan (author), Li, Xueyuan (author), Liu, Qi (author), Li, Z. (author), Gao, Xin (author)
In the autonomous driving process, the decision-making system is mainly used to provide macro-control instructions based on the information captured by the sensing system. Learning-based algorithms have apparent advantages in information processing and understanding for an increasingly complex driving environment. To incorporate the...
journal article 2022
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Lager, I.E. (author), Stumpf, Martin (author), Vandenbosch, Guy A.E. (author), Antonini, Giulio (author)
The late-time evaluation of electromagnetic (EM) field quantities yielded by convolution integrals that combine Green's functions available at discrete time samples and strictly causal excitations is critically revisited. A typical situation is used for tracing the causes of the divergent late-time behavior that is often experienced. A...
journal article 2022
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Pasqualetto Cassinis, L. (author), Menicucci, A. (author), Gill, E.K.A. (author), Ahrns, Ingo (author), Sanchez-Gestido, Manuel (author)
The estimation of the relative pose of an inactive spacecraft by an active servicer spacecraft is a critical task for close-proximity operations, such as In-Orbit Servicing and Active Debris Removal. Among all the challenges, the lack of available space images of the inactive satellite makes the on-ground validation of current monocular...
journal article 2022
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Tapia, Estefania Alexandra (author), Colomé, Delia Graciela (author), Rueda, José L. (author)
Transient stability (TS) and short-term voltage stability (STVS) assessment are of fundamental importance for the operation security of power systems. Both phenomena can be mutually influenced in weak power systems due to the proliferation of power electronic interface devices and the phase-out of conventional heavy machines (e.g., thermal power...
journal article 2022
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Wang, J. (author), Li, Runlong (author), He, Yuan (author), Yang, Yang (author)
In this article, the interference mitigation (IM) problem is tackled as a regression problem. A prior-guided deep learning (DL)-based IM approach is proposed for frequency-modulated continuous-wave (FMCW) radars. Considering the complex-valued nature of radar signals, a complex-valued convolutional neural network, which is different from the...
journal article 2022
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Chang, X. (author), Wu, Jianjun (author), Correia, Gonçalo (author), Sun, Huijun (author), Feng, Ziyan (author)
Carsharing has become a popular travel mode owing to its convenience of use, easy parking, and low cost of using a car by those who only need it occasionally. However, because of the inadequate location of carsharing stations (station-based systems) or vehicles (free-floating systems), effectively requiring expensive and complex relocation...
journal article 2022
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Stops, L. (author), Leenhouts, Roel (author), Gao, Q. (author), Schweidtmann, A.M. (author)
Process synthesis experiences a disruptive transformation accelerated by artificial intelligence. We propose a reinforcement learning algorithm for chemical process design based on a state-of-the-art actor-critic logic. Our proposed algorithm represents chemical processes as graphs and uses graph convolutional neural networks to learn from...
journal article 2022
Searched for: subject%3A%22convolution%22
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