document

Predicting Haemodynamic Instability in Critical Congenital Heart Disease Patients: A Proof of Concept

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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Weight classification during actively assisted elbow flexion and extension

Heyns, Kirsten (author)

Severe muscle weakness is a symptom appearing in certain neuromuscular diseases (NMDs), such as Duchenne Muscular Dystrophy (DMD), affecting people's daily lives by reducing functionality, decreasing independence, and reducing the ability to perform essential daily activities. This patient group might benefit from using active-assistive devices...

master thesis 2023

document

Face image synthesis for robust facial analysis

Marinos, Marios (author)

Emotion recognition is a challenging problem in the field of computer vision. The automatic classification of emotions using facial expressions is a promising approach to understand human behavior in various applications such as marketing, health, and education. How- ever, recognizing some emotions, such as anger, jealousy, contempt, and disgust...

master thesis 2023

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Predictive Analysis of Anti-NMDA-Receptor Encephalitis: using a Random Forest Classifier on EEG Data

Lückerath, Femke (author)

During the initial phase of diagnosis, patients with anti-NDMA-receptor encephalitis (anti-NMDARE) often experience severe symptoms that significantly impact their quality of life. Anti-NDMARE is an autoimmune disorder affecting the brain, with electroencephalography (EEG) playing a vital role in diagnosis and treatment. Identifying EEG patterns...

master thesis 2023

document

Value- Aware Active Learning

Sayin, Burcu (author), Yang, J. (author), Passerini, Andrea (author), Casati, Fabio (author)

In many practical applications, machine learning models are embedded into a pipeline involving a human actor that decides whether to trust the machine prediction or take a default route (e.g., classify the example herself). Selective classifiers have the option to abstain from making a prediction on an example they do not feel confident about...

conference paper 2023

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Employing Deep Ensemble Learning for Improving the Security of Computer Networks against Adversarial Attacks

Nowroozi, Ehsan (author), Mohammadi, Mohammadreza (author), Savas, Erkay (author), Mekdad, Yassine (author), Conti, M. (author)

In the past few years, Convolutional Neural Networks (CNN) have demonstrated promising performance in various real-world cybersecurity applications, such as network and multimedia security. However, the underlying fragility of CNN structures poses major security problems, making them inappropriate for use in security-oriented applications,...

journal article 2023

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Towards a Safer and More Reliable Selective Classifier: With Human Knowledge and Value Incorporated

Chen, Xinyue (author)

While the performance of traditional confidence-based rejectors is heavily dependent on the calibration of the pretrained model, this study proposes the concept of feature-based rejectors and the whole pipeline where such rejector can be used in. Multiple design and development decisions along the implementation are discussed in the paper -...

master thesis 2022

document

A 23-μW Keyword Spotting IC With Ring-Oscillator-Based Time-Domain Feature Extraction

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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Angle-insensitive Human Motion and Posture Recognition Based on 4D imaging Radar and Deep Learning Classifiers

Zhao, Yubin (author), Yarovoy, Alexander (author), Fioranelli, F. (author)

The need for technologies for Human Activity Recognition (HAR) in home environments is becoming more and more urgent because of the aging population worldwide. Radar-based HAR is typically using micro-Doppler signatures as one of the main data representations, in conjunction with classification algorithms often inspired from deep learning...

journal article 2022

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Change Point Detection In Continuous Integration Performance Tests

van der Horst, Tim (author)

Software testing is an integral part of the development of embedded systems. Among other reasons, tests are frequently used to ensure that a system meets all the specifications, which is especially important when designing systems for the medical industry. Software changes that have a detrimental impact on a real-time system's performance can...

master thesis 2021

document

HaarCNN: Detection and Recognition of Comic Strip Characters with Deep Learning and Cascade Classifiers

Kotlicki, Bartlomiej (author)

Object detection and recognition is a computer vision problem tackled with techniques such as convolutional neural networks or cascade classifiers. This paper tackles the challenge of using the similar methods in the realm of comics strips characters. We approached the idea of combining cascade classifiers with various convolutional neural...

bachelor thesis 2021

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The Cancer SENESCopedia: A delineation of cancer cell senescence

Jochems, Fleur (author), Thijssen, Bram (author), De Conti, Giulia (author), Jansen, Robin (author), Pogacar, Ziva (author), Groot, Kelvin (author), Wang, Liqin (author), Schepers, Arnout (author), Wessels, L.F.A. (author)

Cellular senescence is characterized as a stable proliferation arrest that can be triggered by multiple stresses. Most knowledge about senescent cells is obtained from studies in primary cells. However, senescence features may be different in cancer cells, since the pathways that are involved in senescence induction are often deregulated in...

journal article 2021

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To order or not to order: Predicting customer grocery shopping behaviour using multi-label classification techniques

Verbruggen, Roderik (author)

Research and Objective: In the recent years the online grocery sector experienced an enormous uplift and evolved to a highly competitive business sector. Within this demanding environment, the need for strategic information has become extremely important, as it greatly enhances decision-making processes and the optimisation of the supply chain....

master thesis 2020

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Indoor Localization of Bluetooth Low Energy Nodes Surrounded by Random Obstacles and Interference

James, Javier (author)

The company Kien 1 is developing Bluetooth Low Energy (BLE) speakers, consisting of a subwoofer and several satellite speakers. These subwoofer and satellite speakers will have a feature named Follow Me, which when enabled from a smartphone application, will play music only in the room where the user currently is. The BLE’s signals will...

master thesis 2020

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Constrained Concealment Attacks against Reconstruction-based Anomaly Detectors in Industrial Control Systems

Erba, Alessandro (author), Taormina, R. (author), Galelli, Stefano (author), Pogliani, Marcello (author), Carminati, Michele (author), Zanero, Stefano (author), Tippenhauer, Nils Ole (author)

Recently, reconstruction-based anomaly detection was proposed as an effective technique to detect attacks in dynamic industrial control networks. Unlike classical network anomaly detectors that observe the network traffic, reconstruction-based detectors operate on the measured sensor data, leveraging physical process models learned a priori....

conference paper 2020

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A Defect Classication Methodology for Sewer Image Sets with Convolutional Neural Networks

Meijer, D.W.J. (author), Scholten, L. (author), Clemens, F.H.L.R. (author), Knobbe, Arno (author)

Sewer pipes are commonly inspected in situ with CCTV equipment. The CCTV footage is then reviewed by human operators in order to classify defects in the pipes and make a recommendation on possible interventions. This process is both labor-intensive and error-prone. Other researchers have suggested machine learning techniques to (partially)...

journal article 2019

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Cooperative Visual Object Learning

Radojević, Jovana (author)

A lot of attention has recently been focused on possible benefits of the cooperation between machines and humans. Taking the best from machines and humans and joining them together can produce results which exceed each collaborating partner performing separately. A common belief is that the<br/>key for good cooperation is an excellent...

master thesis 2017

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Performance analysis of classification methods for indoor localization in VLC networks

Sánchez-Rodríguez, D. (author), Alonso-González, I. (author), Sánchez-Medina, J. (author), Ley-Bosch, C. (author), Díaz-Vilarino, L. (author)

Indoor localization has gained considerable attention over the past decade because of the emergence of numerous location-aware services. Research works have been proposed on solving this problem by using wireless networks. Nevertheless, there is still much room for improvement in the quality of the proposed classification models. In the last...

conference paper 2017

document

Supporting users with credibility assessments of health Tweets

Post, F. (author)

Twitter is one of the most popular social media platforms nowadays with more than 500 million tweets being send on a daily basis. A great variety of topics is discussed on Twitter and health has become a widely mentioned topic on Twitter. Users share updates regarding their own personal health situation and they use Twitter to look up health...

master thesis 2014

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Continuous Risk Management of Customers, Application at the ING Arrears Department

Van den Bos, G. (author)

Continuous Risk Management (CRM) is a practice in which there is a continuous assessment of the risks that exist or could arise. In addition, in CRM it is determined which risks have priority to be dealt with and strategies are considered that could be implemented to deal with the risks. This thesis demonstrates how CRM of (mortgage) customers...

master thesis 2014