document

Augmented Reality Water Effects Visualization

Dumanlı, Ege (author)

Simulating visually compelling water is difficult especially in Augmented Reality environments where the water has to interact with the user’s surroundings. In this paper, implementations of reflections, refractions and transparency effects that are physically inaccurate but result in visually compelling water simulation in Augmented Reality...

bachelor thesis 2022

document

A proof of concept for aligning sketches to their corresponding painting

Radder, Marit (author)

Aligning sketches to their corresponding painting could give more insight into the creative process of an artist. This is a difficult task that cannot be solved directly with classical image registration techniques. Typically, features such as cracks and brushstrokes are used to match different modalities. A sketch does not contain such...

bachelor thesis 2022

document

Unpaired day-night domain adaptation using CycleGANs combined with CIConv

Streefkerk, Thomas (author)

CycleGANs [1] and CIConv [2] are both relatively new approaches to their respective applications. For CycleGANs this application is unpaired image-to-image domain adaptation and for CIConv this application is making images more<br/>robust to illumination changes. We investigate whether CycleGANs in combination with CIConv can be used to improve...

bachelor thesis 2022

document

A trainable Gaussian color model for determining the color invariant

Gioia, Gianpaolo (author)

The possibility to improve an existing method by making (part of) it learnable is explored in this research. The work that this research extends added prior knowledge to a Convolutional Neural Network (CNN) to improve its performance when dealing with an illumination shift. The method used for the preprocessing, is the color invariant. The...

bachelor thesis 2022

document

Unsupervised Day-Night Domain Adaptation with a Physics Prior for Image Classification

Brouwer, Gees (author)

While deep neural networks show great potential for being part of safety-critical applications such as autonomous driving, covering their sensitivity to illumination shifts by adding training data is of- ten non-trivial. The undesired illumination shift between train and test data can be addressed by domain adaptation methods. Recent work [9]...

bachelor thesis 2022

document

Moral Embeddings: A closer look at their Performance, Generalizability and Transferability

Vecerdea, Dragos (author)

Moral values are abstract ideas that ground our judgements towards what is right or wrong. However, with the rapid unfold of moral rhetoric on social media, it becomes increasingly important to place these ideas in a moral frame, contain their harmful effects, and recognise their positive ones. So far, estimating values from opinionated text has...

bachelor thesis 2021

document

Estimating the transferability of state-of-the-art models in predicting moral values

Dondera, Alin (author)

Moral values play a crucial role in our decision-making process by defining what is right and wrong. With the emergence of political activism and moral discourse on social media, and the latest developments in Natural Language Processing, we are looking at an opportunity to analyze moral values to observe trends as they form. Recent studies have...

bachelor thesis 2021

document

Evaluating catastrophic forgetting of state-of-the-art NLP models for predicting moral values

Arsene, Florentin (author)

Personal moral values represent the motivation behind individuals' actions and opinions. Understanding these values is helpful both in predicting individuals' actions, such as violent protests, and building AI that can better collaborate with humans. Predicting moral values is a challenging problem due to the abstract and subjective essence of...

bachelor thesis 2021

document

Evaluating interpretability of state-of-the-art NLP models for predicting moral values

Constantinescu, Ionut (author)

Understanding personal values is a crucial aspect that can facilitate the collaboration between AI and humans. Nonetheless, the implementation of collaborative agents in real life greatly depends on the amount of trust that is built in their relationship with people. In order to bridge this gap, more extensive analysis of the explainability of...

bachelor thesis 2021

document

Performance analysis of the state-of-the-art NLP models for predicting moral values

Geadău, Andrei (author)

Moral values are instrumental in understanding people's beliefs and behaviors. Estimating such values from text would facilitate the interaction between humans and computers. To date, no comparison between NLP models for predicting moral values from text exists. This paper addresses this by comparing LSTM and more novel models such as BERT and...

bachelor thesis 2021

document

Deep Learning for Stance Detection: A Review and Comparison of the State-of-the-Art Approaches

Roeters van Lennep, Jacob (author)

Stance detection is a Natural Language Processing task that can detect if the input text is in favour, against or neutral towards a target. Research on stance detection has been growing and evolving over the last decade. In this paper, the current approaches for stance detection are discussed with a focus on the deep learning approaches. The...

bachelor thesis 2021

document

Political Stance Detection using Knowledge Graphs and Sentiment Analysis

Van Steenweghen, Abel (author)

Sentiment analysis techniques estimate the opinion of the au- thor of a text towards an entity from that text. Current sen- timent analysis techniques are based on language features or deep learning methods. However, they do not make use of the extensive background knowledge that human readers can have. This makes it difficult for these models...

bachelor thesis 2021

document

A Hybrid Approach for Sentence Similarity: Combining Semantic and Structural Similarity Metrics

Haakman, Wout (author)

Predicting similarity between sentence pairs is essential for applications such as recommender systems and plagiarism detection. There have been several categories of approaches for predicting sentence similarity. This paper combines approaches from two categories, semantic and structural similarity, to find a hybrid approach that aligns more...

bachelor thesis 2021

document

Preparing Stance Detection: Feature Extraction Methods and Their Performance Used for Feature-Based Machine Learning Algorithms

Vass, Kristóf (author)

Stance detection is a Natural Language Processing task that aims to detect the stance (support, agreement, or disagreement) of a piece of text towards some target. In this paper, we aim to find the best performing pair of feature extraction method and feature-based machine learning algorithm. By doing so, an explainable method can be found to...

bachelor thesis 2021

document

Tackling the Headline Incongruity Problem using Stance Detection

Mariën, Simon (author)

The increasing amount of untrusted content on the internet is a worrisome trend. The headline of an article can be adjusted to influence a potential readers attention and click-through rate. This clickbait or sensationalism can mislead the reader as the headline does not accurately represent the information in the corresponding article body....

bachelor thesis 2021

document

Generative RGB-D Face Completion for Head-Mounted Display Removal

Numan, Nels (author)

Virtual reality (VR) creates an exceptional experience in which users can explore virtual environments. Wearing a head-mounted display (HMD), users are able to observe a virtual world that is rendered based on their physical movement and actions. A common solution for capturing the visual and geometric information needed for the construction of...

master thesis 2020

document

Stylization of shadows in ski-panorama maps: A case study on Atelier Novat

Hanagodimath, Anmol (author)

Panorama maps can be defined as aerial-view paintings of geologically complex landscapes that are represented in a convenient manner to non-expert viewers. This thesis focuses on a specific variant of panorama maps known as "ski-panorama maps" or "piste-maps" drawn by the french landscape and panorama artist, Pierre Novat. These maps usually...

master thesis 2020

document

Evaluating Methods for Improving Crowdsourced Annotations of Images Containing Lego Bricks

Oltmans, Rembrandt (author)

Data collection by means of crowdsourcing can be costly or produce inaccurate results. Methods have been proposed for solving these problems. However, it remains unclear what methods work best in scenarios with multiple similar objects of interest present in the same image, which is important for training computer vision with applications such...

bachelor thesis 2020

document

Faster R-CNN as an Application for Object Detection of Scattered LEGO Pieces

Abderrazik, Hiba (author)

The benchmarks for the accuracy of the best performing object detectors to date are usually based on homogeneous datasets, including objects such as vehicles, people, animals and foods. This excludes a whole set of scenarios containing small, cluttered and rotated objects. This paper selects a state-of-the-art object detection model, Faster R...

bachelor thesis 2020

document

The Current State of the Art in Multi-Label Image Classification Applied on LEGO Bricks

Tahur, Nishad (author)

This paper shows how the current state of the art in image classification performs on LEGO bricks. Currently the standard image classification models with deep learning are single label image classifiers. In this paper we will convert them to work on multi-label images and subsequently evaluate how well they perform. We show how well the...

bachelor thesis 2020