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Piccoli, Francesco (author)
Recent advancements in machine learning (ML) have shown promise in accelerating polymer discovery by aiding in tasks such as virtual screening via property prediction, and the design of new polymer materials with desired chemical properties. However, progress in polymer ML is hampered by the scarcity of high-quality, labelled datasets, which are...
master thesis 2024
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Dondera, Alin (author)
Masked Autoencoders (MAEs) represent a significant shift in self-supervised learning (SSL) due to their independence from augmentation techniques for generating positive (and/or negative) pairs as in contrastive frameworks. Their masking and reconstruction strategy also aligns well with SSL approaches in natural language processing. Most MAEs...
master thesis 2024
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van Winden, Brian (author)
Introduction<br/>Approximately 9 in 1000 children are born with congenital heart disease (CHD), of whom a quarter are classified as critical CHD (CCHD) and require an intervention within their first year. Monitoring these patients in the Paediatric Intensive Care Unit (PICU) is crucial, yet with increasing amounts of data, detecting subtle...
master thesis 2024
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Rijpkema, Gerben (author)
Forensic microtrace investigation relies on a time- and labour-intensive process of manually analysing samples via microscopy. To aid forensic experts in their investigations, an image recognition model for microtrace localisation and classification is needed. This work investigates the trace recognition accuracy that can be achieved by...
master thesis 2024
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Sebus, Siert (author)
The Deep Neural Network (DNN) has become a widely popular machine learning architecture thanks to its ability to learn complex behaviors from data. Standard learning strategies for DNNs however rely on the availability of large, labeled datasets. Self-Supervised Learning (SSL) is a style of learning that allows models to also use unlabeled data...
master thesis 2024
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Dong, Y. (author), Lu, Xingmin (author), Li, Ruohan (author), Song, Wei (author), van Arem, B. (author), Farah, H. (author)
The burgeoning navigation services using digital maps provide great convenience to drivers. However, there are sometimes anomalies in the lane rendering map images, which might mislead human drivers and result in unsafe driving. To accurately and effectively detect the anomalies, this paper transforms lane rendering image anomaly detection into...
poster 2024
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Coraddu, A. (author), Oneto, Luca (author), Walker, J.M. (author), Patryniak, Katarzyna (author), Prothero, Arran (author), Collu, Maurizio (author)
The global installed capacity of floating offshore wind turbines is projected to increase by at least 100 times over the next decades. Station-keeping of floating offshore renewable energy devices is achieved through the use of mooring systems. Mooring systems are exposed to a variety of environmental and operational conditions that cause...
journal article 2024
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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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Moradi, M. (author), Gul, F.C. (author), Zarouchas, D. (author)
Developing comprehensive health indicators (HIs) for composite structures encompassing various damage types is challenging due to the stochastic nature of damage accumulation and uncertain events (like impact) during operation. This complexity is amplified when striving for HIs independent of historical data. This paper introduces an AI...
journal article 2024
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Ferede, R. (author), de Croon, G.C.H.E. (author), de Wagter, C. (author), Izzo, Dario (author)
Developing optimal controllers for aggressive high-speed quadcopter flight poses significant challenges in robotics. Recent trends in the field involve utilizing neural network controllers trained through supervised or reinforcement learning. However, the sim-to-real transfer introduces a reality gap, requiring the use of robust inner loop...
journal article 2024
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Viswanathan, V. (author), Mohania, Mukesh (author), Goyal, Vikram (author)
Online learning systems have multiple data repositories in the form of transcripts, books and questions. To enable ease of access, such systems organize the content according to a well defined taxonomy of hierarchical nature (subject - chapter -topic). The task of categorizing inputs to the hierarchical labels is usually cast as a flat multi...
journal article 2024
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Beltman, Maarten (author)
Punctuality is a key performance indicator for any airline. Hub-and-spoke airlines are particularly committed to on-time arrivals to guarantee passenger connections. Flights that are delayed at departure need to compensate for the lost time whilst airborne. Because fueling takes place well before scheduled departure, predicted departure delays...
master thesis 2023
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Beţianu, Miruna (author)
Large language models (LLMs) increasingly serve as the backbone for classifying text associated with distinct domains and simultaneously several labels (classes). When encountering domain shifts, e.g., classifier of movie reviews from IMDb to Rotten Tomatoes, adapting such an LLM-based multi-label classifier is challenging due to incomplete...
master thesis 2023
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Kazmi, Syed Baqir Ali (author)
This dissertation endeavors to introduce a novel supervised Structural Health Monitoring (SHM) methodology for the detection of damage and the prediction of fatigue life in asphalt concrete materials. Grounded in the principles of S-N (strain-number of cycles until failure) curves, this research addresses the intricate task of proficiently...
master thesis 2023
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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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Liu, Kevin (author)
This master’s thesis explores the application of Self-Supervised Contrastive Learning (SSCL), specifically the SimCLR algorithm, to enhance feature representation learning from Wafer Bin Maps (WBM) in the semiconductor manufacturing process. The motivation stems from the industry’s growing need for automated defect detection and root-cause...
master thesis 2023
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Smeenk, Rutger (author)
This research aims at quantifying the uncertainty in the predictions of tensor network constrained kernel machines, focusing on the Canonical Polyadic Decomposition (CPD) constrained kernel machine. Constraining the parameters in the kernel machine optimization problem to be a CPD results in a linear computational complexity in the number of...
master thesis 2023
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Xu, Y. (author)
Micro air vehicles (MAVs) have shown significant potential in modern society. The development in robotics and automation is changing the roles of MAVs from remotely controlled machines requiring human pilots to autonomous and intelligent robots. There is an increasing number of autonomous MAVs involved in outdoor operations. In contrast, the...
doctoral thesis 2023
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Poulakakis Daktylidis, Stelios (author)
There exists a fundamental gap between human and artificial intelligence. Deep learning models are exceedingly data hungry for learning even the simplest of tasks, whereas humans can easily adapt to new tasks with just a handful of samples. Unsupervised few-shot learning (U-FSL) aspires to bridge this gap, without relying on costly annotations....
master thesis 2023
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Mendoza Silva, Santiago (author)
Bacterial identification is crucial for addressing infectious diseases and enabling effective treatment strategies. Conventional bacteria identification methods like MALDI-TOF, while efficient, lack the capability for screening the effectiveness of antibiotics. On the other hand, existing antimicrobial resistance (AMR) tests, despite being...
master thesis 2023
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