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Roldan Montero, I. (author), Fioranelli, F. (author), Yarovoy, Alexander (author)
A novel framework to enhance the angular resolution of automotive radars is proposed. An approach to enlarge the antenna aperture using artificial neural networks is developed using a self-supervised learning scheme. Data from a high angular resolution radar, i.e., a radar with a large antenna aperture, is used to train a deep neural network...
journal article 2023
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Wen, J. (author), Abeel, T.E.P.M.F. (author), de Weerdt, M.M. (author)
Global soft fruit supply chains rely on trustworthy descriptions of product quality. However, crucial criteria such as sweetness and firmness cannot be accurately established without destroying the fruit. Since traditional alternatives are subjective assessments by human experts, it is desirable to obtain quality estimations in a consistent and...
journal article 2023
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Sun, W. (author), Katsifodimos, A (author), Hai, R. (author)
The rapid growth of large-scale machine learning (ML) models has led numerous commercial companies to utilize ML models for generating predictive results to help business decision-making. As two primary components in traditional predictive pipelines, data processing, and model predictions often operate in separate execution environments,...
conference paper 2023
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Difrancesco, S. (author), van Baardewijk, J.U. (author), Cornelissen, A.S. (author), Varon, Carolina (author), Hendriks, R.C. (author), Bouwer, A.M. (author)
Wearable sensors offer new opportunities for the early detection and identification of toxic chemicals in situations where medical evaluation is not immediately possible. We previously found that continuously recorded physiology in guinea pigs can be used for early detection of exposure to an opioid (fentanyl) or a nerve agent (VX), as well as...
journal article 2023
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Kruse, N.C. (author), Fioranelli, F. (author), Yarovoy, Alexander (author)
Due to numerous benefits, radar is considered as an important sensor for human activity classification. The problem of classifying continuous sequences of activities of unconstrained duration has been studied in this work. To tackle this challenge, a radar data processing method utilizing point transformer networks has been proposed. The method...
conference paper 2023
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Hadjisotiriou, George (author), Mansour Pour, K. (author), Voskov, D.V. (author)
In this study, we utilize deep neural networks to approximate operators of a nonlinear partial differential equation (PDE), within the Operator-Based Linearization (OBL) simulation framework, and discover the physical space for a physics-based proxy model with reduced degrees of freedom. In our methodology, observations from a high-fidelity...
conference paper 2023
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Hadjisotiriou, George (author)
Compositional simulation is computationally intensive for high-fidelity models due to thermodynamic equilibrium relations and the coupling of flow, transport and mass transfer. In this report, two methods for accelerated compositional simulation are outlined and demonstrated for a gas vaporization problem. The first method uses a proxy model...
master thesis 2022
document
van Schijndel, Jessie (author)
The workflow of a data science practitioner includes gathering information from different sources and applying machine learning (ML) models. Such dispersed information can be combined through a process known as Data Integration (DI), which defines relations between entities and attributes. When all information is combined in one source suited...
master thesis 2022
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CHENG, ZHIMIN (author)
A wide range of practical problems involve computing multi-dimensional integrations. However, in most cases, it is hard to find analytical solutions to these multi-dimensional integrations. Their numerical solutions always suffer from the `curse of dimension', which means the computational complexity grows exponentially with respect to the...
master thesis 2022
document
Lammerts, Philippe (author)
Hate speech detection on social media platforms remains a challenging task. Manual moderation by humans is the most reliable but infeasible, and machine learning models for detecting hate speech are scalable but unreliable as they often perform poorly on unseen data. Therefore, human-AI collaborative systems, in which we combine the strengths of...
master thesis 2022
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TSAKIRAKIS, GIORGOS (author)
Small UAVs and in particular the class of micro-UAVs, whose mass is below 2 kg, are constantly rising in popularity for personal as well as professional use, since they are beneficial in many fields such as defense, transportation, monitoring and agriculture. In spite of their advantages, UAVs can be used for terrorist attacks to fly over...
master thesis 2022
document
den Hertog, Koen (author)
Parkinson’s Disease is a neurodegenerative disease that has a decline in motor behaviour as one of its main symptoms. This decline is currently monitored using subjective measures, such as questionnaires and clinical observations. More detailed and objective tracking of this decline can improve treatment of the disease and allow for earlier...
master thesis 2022
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ZHANG, ZIFAN (author)
Damages within asphalt have been interesting phenomena in asphalt engineering, the detection of which is significant for maintenance of road sections. This project focuses on cracks and delaminations. An attempt was made to filter radar image data with a method based on a VNA-antenna-multilayered system model as well as the data from two...
master thesis 2022
document
Narchi, William (author)
This paper presents how a convolutional neural network can be constructed in order to recognise gestures using photodiodes and ambient light. A number of candidates are presented and evaluated, with the most performant being adopted for in-depth analysis. This network is then compressed in order to be ran on an Arduino Nano 33 BLE...
bachelor thesis 2022
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van Gelder, Daniël (author)
Increased urbanisation has led to significant challenges for public transport operators. Inconsistent demand leads to peaks in passenger activity on the network. Moreover, the COVID-19 pandemic has introduced a need for social distancing as well, limiting the desired capacity of vehicles. To combat this, intelligent real-time and data-driven...
master thesis 2022
document
Buszydlik, Aleksander (author)
Algorithmic recourse aims to provide individuals affected by a negative classification outcome with actions which, if applied, would flip this outcome. Various approaches to the generation of recourse have been proposed in the literature; these are typically assessed on statistical measures such as the validity of generated explanations or their...
bachelor thesis 2022
document
Dobiczek, Karol (author)
Employing counterfactual explanations in a recourse process gives a positive outcome to an individual, but it also shifts their corresponding data point. For systems where models are updated frequently, a change might be seen when recourse is applied, and after multiple rounds, severe shifts in both model and domain may occur. Algorithmic...
bachelor thesis 2022
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Nguyen, Dean (author)
Learning curves have been used extensively to analyse learners' behaviour and practical tasks such as model selection, speeding up training and tuning models. Nonetheless, we still have a relatively limited understanding of the behaviour of learning curves themselves, in particular, whether there exists a parametric function that can best model...
bachelor thesis 2022
document
Kargul, Radek (author)
Spending time in front of screens has become an inescapable activity, which might be interrupted by unrelated external causes. While automatic approaches to identify mind-wandering (MW) have already been investigated, past research was done with self-reports or physiological data. This work explores automated detection utilizing solely facial...
bachelor thesis 2022
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Lek, Gert (author)
The application of machine learning in daily life requires interpretability and robustness. In this paper we try to make the process of building robust and interpretable decision trees more accessible. We do this by making the fitting of these models cheaper and simpler. We build on previous research and see if changing input data or the fitting...
bachelor thesis 2022
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