Spatio-temporal Embedding in Deep Learning for Algal Bloom Forecasting

By Kerem Bayraktar

Algal Bloom Forecasting: Classical Machine Learning versus Deep-Learning

By Rob Lubbers

Algal Bloom Forecasting in a Classification and Regression Setting

By Rodrigo Alvarez Lucendo

Algal Bloom Forecasting using Remote Sensing: Discovering the most predictive data modalities for Algal Bloom Forecasting

By Tolga Gökçe

Blockchain-based machine learning solutions for secure Internet of Things Networks

Supervisors: Chhagan Lal, Mauro Conti

Privacy Protection and Performance Enhancement in IoT Applications using Blockchain and Machine Learning Techniques

By Jeroen Janssen

Mitigating IoT Data Management Security Concerns through Blockchain and Machine Learning Based Solutions: Study and Conceptual Design

By Lars van den Eeden

Blockchain-empowered federated learning based solutions for Internet of Things Security, Privacy, and Performance

By Panagiotis Papadopoulos

Improving security and efficiency in IoT data management using BC based solutions

By Ruben Couwenberg

Machine Learning-based Techniques for Secure and Efficient IoT Data Management

By Tim Kramer

Children and Recommender Systems

Supervisors: M.S. Pera

The Words are not Enough

By Mees van Smaalen

Metadata, the undiscovered treasure box for book recommender systems for children

By Mohamad Awab Alkhiami

Trait Analysis to Facilitate Children's Books Recommender Systems

By Stijn Swart

Covering Covers

By Yessin Beyhan

Exploring the Impact of Different Traits on Children’s Book Recommendations

By Ziang Qiu

Dataset Watermarking

Supervisors: Zekeriya Erkin, Devris Isler

Extended Geometry based Watermarking of 3D Meshes.

By Jaden Nierop

Image watermarking for Machine Learning datasets

By Palle Maesen

Detect the watermark through the training model

By Ruonan Li

Graph database watermarking using pseudo nodes

By Tsvetomir Hristov

Detecting Concept Drift in Deployed Machine Learning Models

Supervisors: Lorena Poenaru-Olaru, Jan Rellermeyer

Margin Density Based Drift Detection - a comparative study

By Baptiste André

How well do clustering similarities-based concept drift detectors identify concept drift in case of synthetic/real-world data?

By Jindřich Pohl

Evaluating Data Distribution Based Concept Drift Detectors

By Konsta Kanniainen

Analysis of Mixed Concept Drift Detectors in Deployed Machine Learning Models

By Toma Zamfirescu

Explaining Deep Learning Models for Fact-Checking

Supervisors: Avishek Anand, Lorenzo Corti, Lijun Lyu

Evaluating Feature Attribution Methods: an Usecase on a Neural Fact-checking Model

By Annabel Simons

A Comparison of Instance Attribution Methods - Comparing Instance Attribution Methods to Baseline k-Nearest Neighbors Method

By Evan de Kruif

Finding Shortcuts to a black-box model using Frequent Sequence Mining

By Jean-Paul Smit

How do different explanation presentation strategies of feature and data attribution techniques affect non-expert understanding?

By Shivani Singh

Support for Room Acoustics Design

Supervisors: Jorge Martinez Castaneda, Elmar Eisemann

Optimisation of Subwoofer Placement using a Finite-Difference Time-Domain Acoustic Simulation

By Delano Flipse

Improving accuracy of sound reflection estimation using neural networks

By Ekko Scholtens

An Analysis of the Computational Efficiency Gains from the Incorporation of Importance Sampling in Determining Optimal Sound Source Location

By Joshua Azimullah