Searched for: subject%3A%22Recurrent%255C+Neural%255C+Networks%22
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van de Kamp, Lars (author), Reinders, Joey (author), Hunnekens, Bram (author), Oomen, T.A.E. (author), van de Wouw, Nathan (author)
Patient-ventilator asynchrony is one of the largest challenges in mechanical ventilation and is associated with prolonged ICU stay and increased mortality. The aim of this paper is to automatically detect and classify the different types of patient-ventilator asynchronies during a patient's breath using the typically available data on...
journal article 2024
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Josemans, Sabine (author)
Introduction<br/>In the Netherlands, approximately five thousand people are dependent on maintenance hemodialysis (HD) treatment. The one-year mortality of this patient population in 2021 was as high as 18%. A significant contributor to this high mortality and burden on HD patients is the high incidence of intradialytic hypotension (IDH), which...
master thesis 2023
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Wu, Yizhuo Wu (author)
With the advancement of 5G/6G radio networks, the demand for high-performance power amplifiers (PAs) with clean spectra and compact constellations has increased significantly. To address these challenges, Artificial Intelligence (AI)-based digital predistortion (DPD) has emerged as a promising approach to linearize radio-frequency (RF) PAs....
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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Dam, Erwin (author)
Various pathologies can occur when independent learners are used in cooperative Multi-Agent Reinforcement Learning. One such pathology is Relative Overgeneralisation, which manifests when a suboptimal Nash Equilibrium in the joint action space of a problem is preferred over an optimal Equilibrium. Approaches exist to combat relative...
master thesis 2022
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Lipski, Matthew (author)
Touching physical buttons to interact with public electronic devices has raised some concerns regrading disease transmission following the COVID-19 pandemic. The use of hand gestures as a touchless replacement sounds appealing, but comes with the challenge of recognizing which gesture is being performed by the user, with only the processing...
bachelor thesis 2022
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Kortekaas, Steven (author)
This thesis investigates the application of machine learning models on foreign exchange data around the WM/R 4pm Closing Spot Rate (colloquially known as the WMR Fix). Due to the nature of the market dynamics around the WMR Fix, inefficiencies can occur and therefore some predictability might be expected. We aim to find these inefficiencies....
master thesis 2022
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Du, XIANGYU (author)
Earthquake prediction has raised many concerns nowadays, due to the massive loss caused by earthquakes, as well as the significance of accurate forecasting. Lots of trials have been investigated and experimented but few achieved satisfying results on short-term prediction (i.e., usually those earthquakes that will happen in three months). It is...
bachelor thesis 2022
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Altena, Anique (author)
Loss-of-control (LOC) is the main cause of crashes for drones. On-board prevention systems should be designed that require low computing power and memory. Data-driven techniques serve as a solution. This study proposes the use of recurrent neural networks (RNN) for LOC prediction. The aim is to identify which RNN model is most suitable and if...
master 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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Köylü, T.C. (author), Reinbrecht, Cezar (author), Brandalero, Marcelo (author), Hamdioui, S. (author), Taouil, M. (author)
Fault injection attacks are a threat to all digital systems, especially to the ones conducting security sensitive operations. Recently, the strategy of observing the instruction flow to detect attacks has gained popularity. In this paper, we provide a comparative study between three hardware-based techniques (i.e., recurrent neural network (RNN)...
journal article 2022
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Sun, Junzi (author), Dijkstra, T.L.E. (author), Aristodemou, K. (author), Buzeţelu, V.S. (author), Falat, T. (author), Hogenelst, T.G. (author), Prins, N. (author), Slijper, B.C. (author)
In this paper, we propose open machine learning models that can provide airport delay predictions in a network with an error of around or less than five minutes. Due to the complexity of different components of air traffic networks, traditional flight performance model-based predictions fall short when dealing with numerous flights and often are...
conference paper 2022
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Conroy, Philip (author), van Diepen, S.A.N. (author), Van Asselen, Sanneke (author), Erkens, Gilles (author), van Leijen, F.J. (author), Hanssen, R.F. (author)
Phase unwrapping, also known as ambiguity resolution, is an underdetermined problem in which assumptions must be made to obtain a result in SAR interferometry (InSAR) time series analysis. This problem is particularly acute for distributed scatterer InSAR, in which noise levels can be so large that they are comparable in magnitude to the...
journal article 2022
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Suau, M. (author), He, J. (author), Congeduti, E. (author), Starre, R.A.N. (author), Czechowski, A.T. (author), Oliehoek, F.A. (author)
Due to its perceptual limitations, an agent may have too little information about the environment to act optimally. In such cases, it is important to keep track of the action-observation history to uncover hidden state information. Recent deep reinforcement learning methods use recurrent neural networks (RNN) to memorize past observations....
journal article 2022
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Kim, Kwantae (author), Gao, C. (author), Graca, Rui (author), Kiselev, Ilya (author), Yoo, Hoi Jun (author), Delbruck, Tobi (author), Liu, Shih Chii (author)
This article presents the first keyword spotting (KWS) IC that uses a ring-oscillator-based time-domain processing technique for its analog feature extractor (FEx). Its extensive usage of time-encoding schemes allows the analog audio signal to be processed in a fully time-domain manner except for the voltage-to-time conversion stage of the...
journal article 2022
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Basien, Henricus (author)
This MSc. thesis presents the extensive research conducted on designing neural networks capable of generating reactionary dance motions. The research was conducted in collaboration with Stichting Another kind of Blue (AKOB) and CompactCopters UG (CC). It is set within the industry context of the ’AI-man’ project, developed...
master thesis 2021
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Zhang, Mirijam (author)
Schema therapy is a type of psychological treatment for people suffering from personality disorders. A schema is a core psychological state of mind that influences external behaviour through the development of coping styles. Current schema therapy is time inefficient and human-processed. Enabling automatic schema classification helps the overall...
bachelor thesis 2021
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Cuperman Coifman, Rafael (author)
been given to Human Activity Recognition (HAR) based on signals obtained by IMUs placed on different body parts. This thesis studies the usage of Deep Learning-based models to recognize different football activities in an accurate, robust, and fast manner. Several deep architectures were trained with data captured with IMU sensors placed on...
master thesis 2021
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Simons, Koen (author)
As traffic demands are ever increasing and building new infrastructure poses challenges in densely populated areas, it is important to optimally utilise existing infrastructure. Short-term traffic forecasting can help with this task, as its predictions can help to prevent congestion by rerouting vehicles. Recently, neural networks developed for...
master thesis 2021
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van den Heuvel, Stefan (author)
Inertial measurement units (IMUs) are getting more and more incorporated into our lives due to their improving accuracy, lower cost and smaller sizes. Applications for inertial-based orientation estimation can already be found in the field of computer vision, aerospace engineering, robotics, navigation, biomechanics, health monitoring and sports...
master thesis 2021
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