Searched for: subject%3A%22contrast%22
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Burr, Zach (author)
Planet formation is a topic that still has many unanswered questions, particularly regarding the formation of wide orbit giant planets. Detecting more of these types of planets can aid understanding of how they form by giving examples of what kind of planets exist. Direct imaging is uniquely well suited to detecting these kinds of planets, which...
master thesis 2024
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Sebus, Siert (author)
The Deep Neural Network (DNN) has become a widely popular machine learning architecture thanks to its ability to learn complex behaviors from data. Standard learning strategies for DNNs however rely on the availability of large, labeled datasets. Self-Supervised Learning (SSL) is a style of learning that allows models to also use unlabeled data...
master thesis 2024
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Edelman, Jory (author)
Magnetic resonance electrical properties tomography is a type of quantitative magnetic resonance imaging that aims to reconstruct the conductivity and permittivity of biological tissue. These electrical properties of the tissue can be used to compute the specific absorption rate, to differentiate tumours from healthy tissue and for hyperthermia...
master thesis 2023
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Möllers, Alex (author)
In this thesis we develop a Bayesian approach to graph contrastive learning and propose a new uncertainty measure based on the disagreement in likelihood due to different positive samples. Moreover, we extend contrastive learning to simplicial complexes and show that it can be used to generate high-quality representations of edge flow data.
master thesis 2023
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Liu, Kevin (author)
This master’s thesis explores the application of Self-Supervised Contrastive Learning (SSCL), specifically the SimCLR algorithm, to enhance feature representation learning from Wafer Bin Maps (WBM) in the semiconductor manufacturing process. The motivation stems from the industry’s growing need for automated defect detection and root-cause...
master thesis 2023
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Park, Jeongwoo (author)
Moral values influence humans in decision-making. Pluralist moral philosophers argue that human morality can be represented by a finite number of moral values, respecting the differences in moral views. Recent advancements in NLP show that language models retain a discernible level of knowledge in deontological ethics and moral norms of society....
master thesis 2023
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Spengler, Daniel (author)
The study of tumor microenvironments (TMEs) and immune cell composition in cancer, a disease characterized by uncontrolled growth and spread of tumor cells, has become increasingly important for understanding tumor progression and patient outcomes. Tools such as the TME-Analyzer enable this kind of research, but their manual workflows highlight...
master thesis 2023
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Galjaard, Jeroen (author)
Few-shot learning presents the challenging problem of learning a task with only a few provided examples. Gradient-Based Meta-Learners (GBML) offer a solution for learning such few-shot problems. These learners approach the few-shot problem by learning an initial parameterization that requires only a few adaptation steps for new tasks. Although...
master thesis 2023
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Goedhart, Aisha (author)
Primary liver cancer is a commonly diagnosed cancer and accurate diagnosis is crucial for treatment planning. To differentiate between malignant and benign liver tumors, contrast-enhanced MRI is typically used as it provides information over multiple contrast phases. However, diagnosis based on MRI is challenging. In this study, automatic...
master thesis 2023
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van Oosterhoudt, Ruben (author)
Introduction: Magnetic Resonance Imaging is a commonly used technique for the initial diagnosis of gliomas. T1, T2, T2-FLAIR, and post-contrast T1 with gadolinium-based contrast agents (GBCAs) can show tumor characteristics. However, using this contrast agent poses a risk to patients with kidney failures, has environmental impact, and increases...
master thesis 2023
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Cui, Jianfeng (author)
We explored the possibility of improving cross-view matching performance with self-supervised learning techniques and perform interpretations in terms of the embedding space of image features. The effect of pre-training by contrastive learning is verified quantitatively by experiments, and also exhibited by visualization of the feature space.
master thesis 2023
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van Ooijen, Lisanne (author)
In the Netherlands, over 12% of the population has chronic kidney damage resulting in about 2000 patients with renal failure each year. Replacement of the kidney function by transplantation is desired, but due to a shortage of donor kidneys, the waiting list for a transplant is...
master thesis 2022
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Fu, Yuan (author)
Facial expression recognition on head-mounted devices (HMDs) is an intriguing research field because of its potential in various applications, such as interactive virtual reality video meetings. Existing work focuses on building a supervised learning pipeline that utilizes a vast amount of labeled periocular images taken by the built-in cameras....
master thesis 2022
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Teeuwen, Tom (author)
<b>OBJECTIVE </b>This study aims to compare non-invasive real-time optical imaging and measuring methods for the quantification of microcirculation of organs during normothermic machine perfusion (NMP). This could help to determine which method is most promising for further development towards a clinical objective transplantability assessment...
master thesis 2022
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Zeng, Liang (author)
Self-supervised contrastive learning has achieved remarkable performance in computer vision. Its success relies on certain priors that vary from different tasks and data at hand, e.g, the object-centric prior implied by ImageNet. For segmentation on complex scenes, researchers have introduced salient objects or auxiliary labels as priors to...
master thesis 2022
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Breunissen, Rens (author)
Numerical methods for solving problems with a large contrast in the coefficients are investigated in this report. These types of problems typically appear in basin modeling. Specifically, the deflation and restricted additive Schwarz (RAS) methods are compared for their effectiveness in solving this type of problem in combination with the...
master thesis 2022
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YOO, Chaewon (author)
Every space has its own atmosphere. This atmosphere consists of elements that stimulate a person's various senses, and the person slowly feels the collection of these elements and recognizes them as the atmosphere of space. This study focuses on what elements make up this atmosphere, how they approach and influence people, and how they will be...
master thesis 2021
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Meghana Amaregouda, Meghana (author)
Conventional early-stage breast cancer treatments such as surgery, chemotherapy and external radiotherapy despite their proven short-term efficacy tend to have adverse long-term physiological and psychological implications on the patients. This is primarily due to their inability to spare healthy tissue surrounding the tumor...
master thesis 2021
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van der Woude, Séline (author)
Background: The Fontan procedure is the last of three stages of congenital heart surgery to treat children born with a single ventricle heart defect. In these patients, a balanced hepatic blood flow distribution (HFD) towards both lungs is important, since a lack of “hepatic factor” has been associated with the formation of pulmonary...
master thesis 2020
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Simion-Constantinescu, Andrei (author)
This thesis presents a novel self-supervised approach of learning visual representations from videos containing human actions. Our approach tackles the complex problem of learning without the need of labeled data by exploring to what extent the ideas successfully used for images can be transferred, adapted and extended to videos for action...
master thesis 2020
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