Searched for: subject%3A%22benchmark%255C+study%22
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SHI, MOJI (author)
Dynamic obstacle avoidance remains a crucial research area for autonomous systems, such as Micro Aerial Vehicles (MAVs) and service robots. <br/>Efforts to develop dynamic collision avoidance techniques in unknown environments have proliferated in recent years. While these methods exhibit impressive and reliable performance in simpler...
master thesis 2023
document
Nika, Ioanna (author)
Lineage abundance estimation of SARS-CoV-2 in wastewater is a technique that aims to monitor the lineage prevalence in communities and help contain the COVID-19 pandemic. Lineages are collections of closely related mutants of a virus. It is suggested that the genome sequences of lineages differ across the globe due to random mutations or...
bachelor thesis 2022
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Nair, Ruben (author)
Audio fingerprinting is a technique that allows for fast identification of music. Research concerning this technique first emerged around the 2000s and has lead to several applications, like Shazam. More recently, developments in this area have slowed down, even though there are still new challenges emerging. This paper investigates one of these...
bachelor thesis 2021
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van Dijk, Tom (author)
With a growing number of drones, the risk of collision with other air traffic or fixed obstacles increases. New safety measures are required to keep the operation of Unmanned Aerial Vehicles (UAVs) safe. One of these measures is the use of a Collision Avoidance System (CAS), a system that helps the drone autonomously detect and avoid obstacles....
report 2020
document
Gasparis, Giorgos (author)
Recently, Offshore Wind Turbines (OWT) have attracted great attention in an effort to make a shift from fossil-based energy sources towards an enhanced sustainable and renewable energy production. In order to achieve the renewables targets and reduce the cost of wind energy, OWTs are consistently increasing in size. Therefore, research has...
master thesis 2019
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Lago, Jesus (author), De Ridder, Fjo (author), De Schutter, B.H.K. (author)
In this paper, a novel modeling framework for forecasting electricity prices is proposed. While many predictive models have been already proposed to perform this task, the area of deep learning algorithms remains yet unexplored. To fill this scientific gap, we propose four different deep learning models for predicting electricity prices and...
journal article 2018
Searched for: subject%3A%22benchmark%255C+study%22
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