Searched for: +
(41 - 60 of 40,159)

Pages

document
Singh, Shivani (author)
The goal of this paper is to examine how different presentation strategies of Explanainable Artificial Intelligence (XAI) explanation methods for textual data affect non-expert understanding in the context of fact-checking. The importance of understand- ing the decision of an Artificial Intelligence (AI) in human-AI interaction and the need for...
bachelor thesis 2023
document
Kanniainen, Konsta (author)
Various techniques have been studied to handle unexpected changes in data streams, a phenomenon called concept drift. When the incoming data is not labeled and the labels are also not obtainable with a reasonable effort, detecting these drifts becomes less trivial. This study evaluates how well two data distribution based label-independent drift...
bachelor thesis 2023
document
Simons, Annabel (author)
In today's society, claims are everywhere, in the online and offline world. Fact-checking models can check these claims and predict if a claim is true or false, but how can these models be checked? Post-hoc XAI feature attribution methods can be used for this. These methods give scores indicating the influence of the individual tokens on the...
bachelor thesis 2023
document
de Kruif, Evan (author)
In this research, a comparison between different Instance Attribution (IA) methods and k-Nearest Neighbors (kNN) via cosine similarity is conducted on a Natural Language Processing (NLP) machine learning model. The format in which the comparison is made is by way of a human survey and automated similarity comparisons of representative vectors....
bachelor thesis 2023
document
Smit, Jean-Paul (author)
Deep-learning (DL) models could greatly advance the automation of fact-checking, yet have not widely been adopted by the public because of their hard-to-explain nature. Although various techniques have been proposed to use local explanations for the behaviour of DL models, little attention has been paid to global explanations. <br/>In response,...
bachelor thesis 2023
document
Pohl, Jindřich (author)
Concept drift is an unforeseeable change in the underlying data distribution of streaming data, and because of such a change, deployed classifiers over that data show a drop in accuracy. Concept drift detectors are algorithms capable of detecting such a drift, and unsupervised ones detect drift without needing the data’s actual labels, which can...
bachelor thesis 2023
document
Janssen, Jeroen (author)
The Internet of Things (IoT) is producing significant amounts of data. Protecting this data from adversaries is therefore a prominent field of research. This paper conducts a review of the current state-of-the-art in the field of IoT integrated with Blockchain (BC) and Machine Learning (ML). The review focuses on the use of privacy and...
bachelor thesis 2023
document
Butzelaar, Sven (author)
Machine learning can be used to classify patients in a hospital. Here, the classifier has to minimize the cost of misclassifying the patient and minimize the costs of the tests. Unfortunately, obtaining features may be costly, e.g., taking blood tests or doing an x-ray scan. Furthermore, it is possible that acquiring those test results may take...
bachelor thesis 2023
document
van Smaalen, Mees (author)
Reading is an essential skill for any child to learn, and finding enjoyment in it can greatly contribute to developing proper reading comprehension. Finding the books they like could prove to be difficult. Utilizing collaborative filtering recommender systems to recommend books to children is a tricky task, the lack of user feedback makes it...
bachelor thesis 2023
document
Alvarez Lucendo, Rodrigo (author)
Forecasting algal blooms using remote sensing data is less labour-intensive and has better cover- age in time and space than direct water sampling. The paper implements a deep learning technique, the UNet Architecture, to predict the chlorophyll concentration, which is a good indicator for al- gal bloom in the Rio Negro water reservoirs of...
bachelor thesis 2023
document
Gökçe, Tolga (author)
An algal bloom is defined as a rapid increase in common algae (phytoplankton) abundance in water bodies and it can occur when a group of certain environmental factors is combined. If the algae populations grow out of control, such algal blooms become problematic and cause damage to the ecosystem, such phenomena are called harmful algal blooms....
bachelor thesis 2023
document
Kramer, Tim (author)
The dramatic increase in the number of Internet of Things (IoT) devices has created rapid growth for exploitation of security flaws and vulnerabilities. Particularly for critical infrastructure and real-time systems security threats can be highly damaging. Machine Learning (ML) algorithms have demonstrated the ability to combat the security...
bachelor thesis 2023
document
Azimullah, Joshua (author)
A novel approach for determining the optimal location of a sound source within an acoustic environment is proposed. This approach involves the application of Importance Sampling to improve the efficiency of the existing method of acoustic ray-tracing for finding the frequency response at various listening locations. The results of this study do...
bachelor thesis 2023
document
Lubbers, Rob (author)
The aim of this paper is to find out which Machine Learning (ML) model predicts the concentration of Chlorophyll-a, in the Palmar lake in Uruguay best. Currently there are no such models to predict the growth in this lake. The algorithms which will be compared in this paper are a Linear Regression model and the U-Net model. We will compare the...
bachelor thesis 2023
document
Nierop, Jaden (author)
Digital watermarking has been used extensively in media in recent years. Yet, there are still relatively few techniques for watermarking 3D meshes. In this paper we implement a watermarking algorithm proposed by O. Benedens that encodes a bit string in the distribution of the normals of the faces of the mesh and investigate a method to improve...
bachelor thesis 2023
document
Zamfirescu, Toma (author)
Label-independent concept drift detectors represent an emerging topic in machine learning research, especially in models deployed in a production environment where obtaining labels can become increasingly difficult and costly. Concept drift refers to unforeseeable changes in the distribution of data streams, which directly impact the performance...
bachelor thesis 2023
document
Maesen, Palle (author)
The media watermarking technique domain has had the last 30 years to develop itself. The non-media side, however, is a way newer sub-domain. [1] The data-gathering process for machine learning algorithms is a tedious and time consuming task. This becomes worse as the scale of these algorithms increases. Thus, protecting the datasets against...
bachelor thesis 2023
document
Hristov, Tsvetomir (author)
Although digital watermarking has been a well-researched topic for the past decades and has seen numerous implementations for relational databases, it still lacks research for non-relational schema-less databases. In this paper, we explore proposed techniques for non-relational database watermarking and introduce an improved technique for NoSQL...
bachelor thesis 2023
document
Geeraedts, Marie (author)
The Dutch population is facing a housing crisis. This crisis has slowly been affecting housing options in the whole country, but it predominantly shows problems in the densely populated urban regions. In September 2021, approximately 15000 gathered in Amsterdam at a large housing protest: the Woonprotest. This research is an explorative case...
master thesis 2023
document
André, Baptiste (author)
When deployed in production, machine learning models sometimes lose accuracy over time due to a change in the distribution of the incoming data, which results in the model not reflecting reality any longer. A concept drift is this loss of accuracy over time. Drift detectors are algorithms used to detect such drifts. Drift detectors are important...
bachelor thesis 2023
Searched for: +
(41 - 60 of 40,159)

Pages