Building a Deep Cross-media Transfer Network to extract visual relations that relieve the problem of insufficient training data for visual tasks.

Dit interdisciplinair onderzoeksproject verkent verschillende adaptieve machine-learning methoden die inzicht kunnen geven in de interactie tussen mens en machine. Het uiteindelijke doel is een open en natuurlijke communicatie tussen mens en AI die moet resulteren in wederzijds vertrouwen, samenwerking…

Tomography is a powerful technique to non-destructively determine the interior structure of an object.Usually, a series of projection images (e.g.\ X-ray images) is acquired from a range of different positions.

Continuous optimization is never easy: the exact solution is always a luxury demand and the theory of it is not always analytical and elegant.

The invention of neural networks marks a critical milestone in the pursuit of true artificial intelligence. Despite their impressive performance on various tasks, these networks face limitations in learning efficiently as they are often trained from scratch.

This thesis introduces a relational interaction model and a practical tool for describing, visualising and generating interactive dialogues.

Optical projection tomography (OPT) is a tomographic 3D imaging technique used for specimens in the millimetre scale.

This thesis investigates the contribution of quantum computers to machine learning, a field called Quantum Machine Learning. Quantum Machine Learning promises innovative perspectives and methods for solving complex problems in machine learning, leveraging the unique capabilities of quantum computers…

Promotor: Prof.dr.ir. E. Deprettere

De verandering van een gesloten instelling naar een open leefomgeving voor patiënten met een laat stadium van dementie zal de patiënten meer vrijheid geven in hun dagelijks leven. Het effect van deze verandering op de mobiliteit van de patiënten, hun activiteiten en hun interactie met anderen zal worden…

Interactive exploration of large volumes of data is increasingly common, as data scientists attempt to extract interesting information from large opaque data sets. This scenario presents a difficult challenge for traditional database systems, as (1) nothing is known about the query workload in advance,…

We strive to address the challenge of constructing a modeling language to write software which can take advantage of recent hardware developments (multicore, cloud) without compromising in its abstraction levels.

Constraint multi-objective optimization with a limited budget for function evaluations is challenging. This thesis tackles this problem by proposing new optimization algorithms. These algorithms are applied on holistic ship design problems. This helps naval architects balance objectives like cost, efficiency,…

Promotor: J.N. Kok, Co-promotor: C.M. Soares, A.J. Knobbe

The increasing competition in the automotive industry requires the tailored, swift development of technologically sophisticated vehicles. Therefore, the computationally expensive state-of-the-art simulation technologies are combined with optimization algorithms. An example of a real-world optimization…

Mining time series is a machine learning subfield that focuses on a particular data structure, where variables are measured over (short or long) periods of time.

Business Process Model and Notation (BPMN) has become the standard for business processes diagrams.

Prematurely born neonates require, amongst others, pharmaceutical therapy. Dosing guidelines for these therapies are often based on data from term born neonates or older infants, while these are not necessarily similar to prematurely born neonates.

Promotor: Prof.dr. E. Deprettere

Promotores: T.H.W. Bäck, Y. Tan, Co-promotor: M.T.M. Emmerich

Promotor: Prof.dr. B.R. Katzy, Prof.dr. H.J. van den Herik, Prof.dr. G.H. Baltes (University of Applied Sciences Konstanz)

SuperCode: Sustainability PER AI-driven CO-DEsign

Promotor: F. Arbab

Promotor: J.N. Kok, P.E. Slagboom Co-promotor: J.F.J. Laros

Anticipatie op de uitdagingen en voordelen die AI-ondersteunde beoordelingen met zich meebrengen voor de relatie tussen studenten en docenten, de menselijke, evenals sociaal-economische kosten en kansen die zij voor universiteiten creëren.

This thesis applies data mining in commercial settings in the telecommunications industry.

Optimization tasks in practice have multifaceted challenges as they are often black box, subject to multiple equality and inequality constraints and expensive to evaluate.

This thesis seeks to combine two different research topics; Multi-Objective Optimization and Complex Network Analysis.

Promotor: Prof.dr. B.R. Katzy

Predictive maintenance (PdM) is a maintenance policy that uses the past, current, and prognosticated health condition of an asset to predict when timely maintenance should occur.

Throughout the history of computer science, a major challenge has been how to assert that software is free of bugs and works as intended. Software bugs can lead to serious negative impacts on any software system. Throughout the main body of the thesis, we implemented a series of studies on exploring…

This dissertation presents the results of the importance of creativity for ICT-students of Dutch universities of applied sciences (in Dutch: hogescholen), and the functioning of training courses that aim to promote creative abilities is highlighted.

Industrial manufacturing processes, such as the production of steel or the stamping of car body parts, are complex semi-batch processes with many process steps, machine parameters and quality indicators.

Systems are called real-time systems, if the correctness of the system does not only depend on the correctness of the system output but also on whether the output is delivered on time.

A modern ship design process is subject to a wide variety of constraints such as safety constraints, regulations, and physical constraints.

Promotor: Prof.dr. J.N. Kok, Co-Promotor: W.A. Kosters

Modeling and analysis of cyber-physical systems are still challenging. One reason is that cyber-physical systems involve many different parts (cyber or physical), of different nature (discrete or continuous), and in constant interaction via sensing and actuating.

This thesis investigates the application of deep learning techniques in image analysis across various domains, focusing on four main themes: feature extraction, classification, segmentation, and integration, demonstrating the transformative potential of these technologies.

In dit project gebruiken we sociale netwerkanalyse om het gedrag van gebruikers op online fora en bijbehorende marktplaatsen in de tijd te analyseren.

De Universiteit Leiden heeft onderzoeksinstituten gevestigd in Leiden en Den Haag.

Promotor: Ed F. Deprettere, Co-promotor: Todor P. Stefanov

In this PhD-thesis several new and existing data science application are described that are particularly focused on applications for tax administrations.

In this thesis we will explore the use of fuzzy systems theory for applications in bioinformatics.

Combinatorial games are games for two competing players, moving in a turn-by-turn fashion, in which there is no chance nor hidden information⁠. Chess, checkers and the simpler tic tac toe are well-known examples of this class of games, as well as game of go⁠.

Including modelling as part of software development appears to have various benefits.

Humans perceive the real world through their sensory organs: vision, taste, hearing, smell, and touch. In terms of information, we consider these different modesalso referred to as different channels of information or modals.

Over the last decades, aviation safety has improved strongly. As a downside, airline pilots do not have as many opportunities to develop through experience the competencies that they need in critical situations.

Promotors: Prof.dr. T.H.W. Bäck, Prof.dr. B. Sendhoff (Technische Universität Darmstadt)

Promotor: Prof.dr. F.S. de Boer, Co-promotor: D. Clarke