Prone-to-supine breast tumor registration using landmarks

During the preoperative planning for breast-conserving surgery, the surgeon makes use of an MRI scan of the breast cancer patient in the prone position to accurately locate the tumour. However, surgery is performed with the patient in the supine position. The surgeon needs to mentally translate the location of the tumour from the prone position...

Optimization of Design and Monitoring of Immersed Tunnels

Many immersed tunnels have already reached or are about to reach the halfway point of their intended lifespan of 100 years. Around this time, several structural problems were noticed during inspection which have led to performance deterioration and durability issues of the tunnel. Often large- scale maintenance was required to meet the design...

Reconstruction and Rendering of Buildings as Radiance Fields for View Synthesis

In inspection and display scenarios, reconstructing and rendering the entire surface of a building is a critical step in presenting the overall condition of the building. In building reconstruction, most works are based on point clouds because of their enhanced availability. In recent years, neural radiance fields (NeRF) have become a common...

Settlement Behaviour of Heinenoord Tunnel: A Numerical Study

The 1st Heinenoordtunnel is an immersed tube which has been open for service in the Netherlands since 1969. Over the past 50 years, a large and increasing settlement has been measured along the tunnel alignment. The greatest value of settlement (65 mm) occurs in tunnel element 1 from 1978 to 2018. The maximum differential settlement has reached...

Scene Editing using Polarization: Real-World Scene Editing using a Polarization-based Intrinsic Image Decomposition

In the field of computer vision, the difficulty of processing the illumination in an arbitrary scene creates complications for a machine's understanding of the scene. Computer vision algorithms commonly use input images acquired by a camera, where the only measured quantity is the amount of light the camera's sensor receives without any...

Using explanations to improve subjective experience of control in situations of delayed control effects

Problem Statement. The responsibility problem in the AI field has been taken seriously. The point of the problem is how to prevent AI systems from making moral decisions for whom they cannot be held accountable. One of the directions to address the responsibility problem is Meaningful Human Control (MHC). Most of the work focused on theoretical...

Toward Fine-grained Causality Reasoning and Question Answering

This thesis mainly studies the causality in natural language processing. Understanding causality is key to the success of NLP applications, especially in high-stakes domains. Causality comes in various perspectives such as enable and prevent that, despite their importance, have been largely ignored in the literature. In view of the lack of a...

Training a Negotiating Agent through Self-Play

Recent developments in applying reinforcement learning to cooperative environments, like negotiation, have brought forward an important question: how well can a negotiating agent be trained through self-play? Previous research has seen successful application of self-play to other settings, like the games of chess and Go. This paper explores the...

Learning the Problem Representation for Improving Negotiation Strategies

The domains of the negotiation can vary significantly. It is possible that a domain is very cooperative, where both agents can receive a high utility; the opposite is also possible, where the domain is very competitive and the agents cannot both get a high utility. In the same manner, the agents can have different strategies leading to a...

Opponent Modeling in Automated Bilateral Negotiation: Can Machine Learning Techniques Outperform State-of-the-Art Heuristic Techniques?

Automated negotiation agents can highly benefit from learning their opponent’s preferences. Multiple algorithms have been developed with the two main categories being: heuristic techniques and machine learning techniques. Historically, heuristic techniques have dominated the field, but with the recent development in the field of machine learning...

Learning a Latent Representation of the Opponent in Automated Negotiation

This paper introduces a strategy for learning opponent parameters in automated negotiation and using them for future negotiation sessions. The goal is to maximize the agent’s utility while being consistent in its performance over various negotiation scenarios. While a number of reinforcement learning approaches in the field have used Q-learning,...

Improving a Reinforcement Learning Negotiating Agent’s Performance by Extracting Information from the Opponent’s Sequence of Offers

With the prospects of decentralized multi-agent systems becoming more prevalent in daily life, automated negotiation agents have made their place in these collaborative settings. They are an approach to promote communication between the agents in reaching solutions that are better for all involved.<br/><br/>Recent literature has shown great...

Predictive modelling of facial features from DNA

Background: In recent years, attention to the genetic architecture of normal-range variation in facial morphology has risen and through GWAS genetic loci associated with facial morphology have been identified. However these give no insight in how the face is shaped by genetics. To investigate the relationship between the genotype and the...

Learning Analytics of Beginner Programming Assignments for Teachers

Due to the increase in student numbers, the amount of time teachers have for each individual decreases. To keep the quality of the program the same, learning analytics can be utilized to assist teachers to give a better overview of problems which the students are struggling the most with. This work makes use of WebLab data of the Introduction to...