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Peschl, Markus (author)
The field of deep reinforcement learning has seen major successes recently, achieving superhuman performance in discrete games such as Go and the Atari domain, as well as astounding results in continuous robot locomotion tasks. However, the correct specification of human intentions in a reward function is highly challenging, which is why state...
master thesis 2021
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Berg, Chris (author)
In this work, we explore the topic of Machine Learning (ML) in the area of Leakage Assessment (LA), a subsection of the field of Side-Channel Analysis (SCA). We focus on Deep Learning Leakage Assessment (DL-LA), as proposed by Wegener et al., and its relation to the established Test Vector Leakage Assessment (TVLA). We will do this in the...
master thesis 2021
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Yang, Wei-Tse (author)
We present the first deep learning approach to estimate the human skeletal system of the musculoskeletal model from monocular video. The current practice of musculoskeletal modeling relies on a motion capture system and OpenSim. The data is recorded in a restricted environment, and OpenSim workflow for musculoskeletal modeling is costly. Our...
master thesis 2021
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Swaminathan, Sudharshan (author)
Side-channel attacks (SCA) focus on vulnerabilities caused by insecure implementations and exploit them to deduce useful information about the data being processed or the data itself through leakages obtained from the device. There have been many studies exploiting these side-channel leakages, and most of the state-of-the-art attacks have been...
master thesis 2021
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Lusse, Bryan (author)
Long acquisition times impede the routine clinical use of quantitative magnetic resonance imaging (qMRI). qMRI quantifies meaningful tissue parameters in T1-, T2-, and PD-maps, as opposed to conventional (qualitative) weighted MRI (wMRI), which only visualises contrast between tissues. Although methods exist that generate synthetic wMRI from...
master thesis 2021
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Saxena, Mudit (author)
As of 2021, the world economic forum deems cyber-security failures as one of the most potent threats to the world. According to a McAfee report, the cost of cybercrimes in 2020 reached nearly 1 trillion US dollars, which was around 50 percent more than what it was in 2018. Exacerbating the already mammoth financial implication of such a failure...
master thesis 2021
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Kerkhof, Maikel (author)
Deep learning techniques have become the tool of choice for side-channel analysis. In recent years, neural networks like multi-layer perceptrons and convolutional neural networks have proven to be the most powerful instruments for performing side-channel analysis. Recent work on this topic has focused on different aspects of these techniques,...
master thesis 2021
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den Boer, Hans (author)
Recently, interest in the use of deep learning technology for RF applications has increased. However, many of these studies are focused on developing deep learning models for a particular RF application. Therefore this master thesis focuses on the implementation of these kinds of deep learning models by using FPGAs such that these deep learning...
master thesis 2021
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Vallendar, André (author)
Plastic pollution is one of the most challenging global environmental problems. Currently, more than 1000 rivers transport approximately 80% of the plastic influx into the oceans. Naturally, more and more companies are interested in tackling this problem. One of them is Noria Sustainable Innovators, a company based in Delft (Netherlands). It is...
master thesis 2021
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Bai, Qian (author)
Roads in modern cities facilitate different types of users, including car drivers, cyclists, and pedestrians. These different users often have a designated section of the road to operate on. Road management, e.g., by municipalities, needs to take this sectioning into account, preferably in an efficient way. Mobile laser scanning (MLS) point...
master thesis 2021
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Doppenberg, Wouter (author)
The resurgence of interest in landing on the Moon has sparked the creation of a number of novel technologies concerning Terrain-Relative Navigation (TRN) algorithms. They aid in the need for increasingly precise landing, as well as ensuring fully autonomous operations. To achieve this, most technologies use a ubiquitous feature present on the...
master thesis 2021
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Pronk, Bram (author)
Personalized treatment methods for a complex disease such as cancer benefit from using multiple data modalities from a patient's cancer cells. Multiple modalities allow for analysis of dependencies between complex biological processes and downstream tasks, such as drug response and/or expected survival rate. To this end, it is important to gain...
bachelor thesis 2021
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Latoškinas, Evaldas (author)
Semi-autonomous driving innovations aim to bridge the gap to fully autonomous driving by co-operating with human drivers to lead to optimal choices on who should drive in different scenarios by offering different automation levels. However, in the present day, known semi-autonomous driving solutions do not generalise to every complex case of...
bachelor thesis 2021
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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
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Birkhoff, Marius (author)
To push the boundaries of technology, the world cup football for robots, RoboCup, is organized on a yearly basis since 1997. To push the boundaries of artificial intelligence, a simulated version of the RoboCup, AI World Cup Football, is arranged yearly from 2017. This requires skillful attackers, defenders and goalkeeper. A large part of having...
bachelor thesis 2021
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Prundeanu, Alin (author)
Wheat is among the most important grains worldwide. For the assessment of wheat fields, image detection of spikes atop the plant containing grain is used. Previous work in deep learning for precision agriculture employs the already established object detectors, Faster R-CNN and YOLO, adapted for the given context. However, these models suffer...
bachelor thesis 2021
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van der Loo, Wouter (author)
Coronary artery disease (CAD) is one of the leading causes of death and disability worldwide. In CAD, the coronary arteries, that supply the myocardium with oxygen, are narrowed or even blocked by a process called atherosclerosis. Invasive coronary angiography (ICA) is the gold standard for the diagnosis of CAD, as well as for intraprocedural...
master thesis 2021
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Wielinga, Kevin (author)
Proton therapy is a great way to treat cancer, since protons can concentrate energy on one single spot, which minimises the irradiated healthy tissue. Because of this property protons are sensitive to uncertainties. Since the tumour is not stationary throughout the treatment, multiple scans are essential. With the current dose calculation...
bachelor thesis 2021
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Doodkorte, Pim (author)
Short-term solar forecasting is crucial for large scale implementation of solar energy and plays an important role in grid balancing, energy trading, and power plant operation. Cloud movement is the main source of unpredictability within solar forecasting and can be recorded using All-Sky Imagers. Conventional cloud modelling methods using image...
master thesis 2021
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Albo Martinez, Diego (author)
Serverless computing is an emerging paradigm for structuring applications in such a way that they can benefit from on-demand computing resources and achieve horizontal scalability. As such, it is an ideal substrate for the resource-intensive and often ad-hoc task of training deep learning models. However, the design and stateless nature of...
master thesis 2021
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