We explored how to morphologically classify well-resolved jetted radio-loud active galactic nuclei (RLAGN) in the LOw Frequency Array (LOFAR) Two-metre Sky Survey (LoTSS) using machine learning.

Onderzoeken hoe gegevens afkomstig van draagbare technologieën kunnen worden gebruikt om effectieve gedragsveranderingen te identificeren die hopelijk zullen leiden tot gezondheidsverbeteringen.

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…

With the emergence of online social networks (OSNs), the way people create and share information has changed, which becomes faster and broader than traditional social media.

In this thesis, we have studied cell images from two types of cells, including pollen grains and the immune cells, neutrophils. These images are captured using a bright field microscope and a confocal microscope.

In this dissertation, we study partition-based models that can be used both for interpretable predictive modeling and for understanding data via interpretable patterns.

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.

Computers zijn in staat om ongelooflijk nauwkeurige voorspellingen te doen op basis van machine learning. Met andere woorden, deze computers kunnen zonder tussenkomst leren als ze eenmaal door mensen zijn voorgeprogrammeerd. Bij LIACS verkennen en verleggen we de grenzen van wat een revolutionaire nieuwe…

Promotor: Prof.dr. J.N. Kok, Co-promotor: F.J. Verbeek

Transport inspectorates are looking for novel methods to identify dangerous behavior, ultimately to reduce risks associated to the movements of people and goods. We explore a data-driven approach to arrive at smart inspections of vehicles.

In 2018, the number of mobile phone users will reach about 4.9 billion. Assuming an average of 5 photos taken per day using the built-in cameras would result in about 9 trillion photos annually.

The research of the Applied Mathematics cluster is concerned with such diverse topics as dynamical systems, representation theory, differential equations and pattern recognition.

The Institute of Environmental Sciences has carried out and participates in several projects that deal with the analysis of energy systems.

Learning from small data sets in machine learning is a crucial challenge, especially when dealing with data imbalances and anomaly detection. This thesis delves into the challenges and methodologies of learning from small datasets in machine learning, with a particular focus on addressing data imbalances…

Het onderzoek van dit programma is gecentreerd rond dynamische systemen, functionele analyse en hun interactie.

Overlevingsanalyse is een onderzoeksgebied dat zich richt op het bestuderen van de tijd tot het optreden van een specifieke uitkomst.

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

With the dramatic growth of the image data on the web, there is an increasing demand of the algorithms capable of understanding the visual information automatically.

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.

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

Radiography is an important technique to inspect objects, with applications in airports and hospitals. X-ray imaging is also essential in industry, for instance in food safety checks for the presence of foreign objects.

This thesis advances automata learning, a key area in computer science, with applications in software verification, biological analysis, and autonomous technologies. It explores three main themes: first, it introduces a passive learning algorithm for generating compact probabilistic models from positive…

Promotor: W.Th.F. den Hollander Co-Promotor: F.M. Spieksma

This thesis is based on five papers on several topics.

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

De masteropleiding Cultural Analysis: Literature and Theory van de Universiteit Leiden richt zich op de studie van literatuur vanuit een vergelijkend en theoretisch perspectief, en onderzoekt de literatuur van een breed spectrum van talen en culturen uit de hele wereld.

This thesis mainly focuses on multimodal understanding and Visual Question Answering (VQA) via deep learning methods. For technical contributions, this thesis first focuses on improving multimodal fusion schemes via multi-stage vision-language interactions.

Promotor: Prof.dr. E. Deprettere

Can we develop a platform for raw materials intelligence?

Explaining treatment response variability between and within patients can support treatment and dosing optimization, to improve treatment of individual patients.

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.

Computers zijn in staat om ongelooflijk nauwkeurige voorspellingen te doen op basis van machine learning. Met andere woorden, deze computers kunnen zonder tussenkomst leren als ze eenmaal door mensen zijn voorgeprogrammeerd. Bij LIACS verkennen en verleggen we de grenzen van wat een revolutionaire nieuwe…

Science is typically a patchwork of research contributions without much coordination. Especially in clinical trials, the follow-up studies that we do fail to be the most promising.

This thesis mainly focuses on cross-modal retrieval and single-modal image retrieval via deep learning methods, i.e. by using deep convolutional neural networks.

Promotor: Prof.dr. B. van de Water

Automated Machine Learning (AutoML) is widely used to automatically build a suitable practical Machine Learning (ML) model for an arbitrary real-world problem, reducing the effort of practitioners in the ML development cycle for real-world applications. Optimization is a key part of a typical AutoML…

Time-series forecasting through modelling sequences of temporally dependent observations has many industrial and scientific applications. While machine learning models have been widely used to create time-series forecasting models, creating efficient and performant time-series forecasting models is…

In meta-analysis, heterogeneity often exists between studies. In such cases, it is essential to investigate the sources of heterogeneity and understand the relationship between effect size and study characteristics (i.e., moderators).

Promotores: T.H.W. Bäck, A. Plaat, Co-promotor: F.J. Verbeek

Op welke manier kunnen docenten de betrokkenheid van studenten ondersteunen en vergroten in de context van blended learning?

Het doel van dit promotieonderzoek was te onderzoeken wat leraren zelf willen leren. De centrale onderzoeksvraag luidde: wat, hoe en waarom willen leraren leren? En hangt dit af van hun jaren leservaring en de school waarin ze werken?

D2.2 comprises the in-depth legal analysis of the initial heuristic model, focused on addressing, in more detail, the main legal concerns for data reusers in the European data economy. This detailed analysis of the legal propositions presented in D2.1 is supplemented by an analysis of the technological,…

The chemical and structural heterogeneity of toxoid vaccines makes their analysis challenging. However, detailed insights on a molecular level can be obtained by mass spectrometry.

Analytical tools for environmental design and management in a systems perspective. The combined use of analytical tools.

We have studied shape with a particular focus on the zebrafish model system. The shape is an essential appearance of the phenotype of a biological specimen and it can be used to read out a current state or response or to study gene expression.

D1.2 reports on the findings of an analysis of framework conditions relevant in the context of the data economy from a legal, a socio-economic and a technological perspective. The analysis is a key foundation for the creation of an initial, heuristic model of the European data economy. The deliverable…

Learning about My meaningful Way through life and profession.

Sewer pipes are an essential infrastructure in modern society and their proper operation is important for public health. To keep sewer pipes operational as much as possible, periodical inspections for defects are performed.

We are living in an information era where the amount of image and video data increases exponentially.