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van Thiel, Erwin (author)Abstract—Multi-label classification is an important branch of classification problems as in many real world classification scenarios an object can belong to multiple classes simultaneously. Deep learning based classifiers perform well at image classifica- tion but their predictions have shown to be unstable when subject to small input...master thesis 2022
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Guo, Zhongyuan (author)Today, with increasingly aging population, healthcare systems in many countries need to improve their effectiveness, and the automatic HAR technology can be beneficial. This can provide early diagnosis of changes in behavioral patterns in the home environment, without hospitalization, and detect critical events such as falls in a timely manner....master thesis 2022
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Reinhard, Marko (author)To meet global market demands, it will remain important to further scale up photovoltaics (PV) production. During the production of solar cells, several defects can occur. Current approaches in quality inspection are reaching their speed limits. This thesis project evaluates the feasibility of faster quality inspection by using deep learning...master thesis 2022
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Feng, Chengming (author)Deep learning has been widely implemented in industrial inspection, such as damage detection from images. However, training deep networks requires massive data, which is hard to collect and laborious to annotate, especially in the aviation scenario of aircraft engines. To alleviate the demand for annotated data, we create BladeSynth - a large...master thesis 2022
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Dam, Erwin (author)Various pathologies can occur when independent learners are used in cooperative Multi-Agent Reinforcement Learning. One such pathology is Relative Overgeneralisation, which manifests when a suboptimal Nash Equilibrium in the joint action space of a problem is preferred over an optimal Equilibrium. Approaches exist to combat relative...master thesis 2022
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Blankendal, Philip (author)Side-channel attacks leverage the unintentional leakage of information that indirectly relates to cryptographic secrets such as encryption keys. Previous settings would involve an attacker conducting some manual-statistical analysis to exploit this data and retrieve sensitive information from the target. With the adoption of deep learning...master thesis 2022
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Habib, Benjamin (author)Whereas in the past, Distribution Systems played a passive role in connecting customers to electricity, Distribution System Operators (DSOs) will have to take in the future a more active role in monitoring and regulating the network to deal with the new behaviors and dynamics of the system brought by the energy transition. State Estimation, a...master thesis 2022
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Bubberman, Wolf (author)Side-Channel Attacks (SCA) attempt to recover the secret cryptographic key from an electronic device by exploiting the unintended physical leakages of said device. With the devices that are being attacked becoming more sophisticated, so is SCA. In the past few years, the focus of the research in the field of SCA shifted towards the application...master thesis 2022
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HU, YANAN (author)In recent years, the expansion of the Internet has brought an explosion of visual information, including social media, medical photographs, and digital history. This massive amount of visual content generation and sharing presents new challenges, especially when searching for similar information in databases —— Content-Based Image Retrieval ...master thesis 2022
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Al, Elise (author)We present application and developments of qMRI. We reconstructed data from the Prediva Ouderen Extentie (POE) database and calculated quantitative maps. The POE database consists of 29 7 Tesla (T) whole-brain MRI scans, including both male and female participants covering the age group between 80 and 91 years old. We used this data to extend...master thesis 2022
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Al-Kaswan, Ali (author)Reverse engineering binaries is required to understand and analyse programs for which the source code is unavailable. Decompilers can transform the largely unreadable binaries into a more readable source code-like representation. However, many aspects of source code, such as variable names and comments, are lost during the compilation and...master thesis 2022
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de Haro Pizarroso, Gabriel (author)Reinforcement Learning is being increasingly applied to flight control tasks, with the objective of developing truly autonomous flying vehicles able to traverse highly variable environments and adapt to unknown situations or possible failures. However, the development of these increasingly complex models and algorithms further reduces our...master thesis 2022
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Apra, Irène (author)Automated reconstruction of detailed semantic 3D city models is challenging due to the need for high-resolution (HR) and large-scale input datasets, the ambiguous definition of the ensuing model, the intricacy of the processing pipeline, and its costs. Furthermore, existing methods mainly focus on geometry rather than semantics. Detailed...master thesis 2022
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Curzi, Fabio (author)Rain-fed agriculture is the main source of food in Ghana therefore improving quantitative rainfall estimates is essential for local farmers to predict crop growth using vegetation models. Rainfall dynamics in the tropics is an ongoing topic of research due to their complexity and sub-grid precipitation variability. At the same time, tropical...master thesis 2022
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Hermans, Sebastiaan (author)In this thesis, a proof of concept was established for the use of a novel coupled QM-MD approach to modelling metallic (copper) electrode-electrolyte interfaces. SCC-DFTB calculations of the instantaneous electronic structure of a copper electrode were coupled to a classical MD simulation of an electrode-electrolyte interface. The applied QM-MD...master thesis 2022
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de Rijk, Philip (author)Knowledge Distillation (KD) is a well-known training paradigm in deep neural networks where knowledge acquired by a large teacher model is transferred to a small student. KD has proven to be an effective technique to significantly improve the student's performance for various tasks including object detection. As such, KD techniques mostly rely...master thesis 2022
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Tak, Seger (author)Pedestrian trajectory prediction is essential for developing safe autonomous driving systems. Such trajectories depend on various contextual cues, among which surrounding objects. <br/><br/>This work proposes the first pedestrian trajectory prediction method in the 2D on-board domain that models interactions between the pedestrian and...master thesis 2022
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Caceres Tocora, Camilo (author)Semantic segmentation of aerial images is the ability to assign labels to all pixels of an image. It proves to be essential for various applications such as urban planning, agriculture and real-estate analysis. Deep Learning techniques have shown satisfactory results in performing semantic segmentation tasks. Training a deep learning model is an...master thesis 2022
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Dirks, Rutger (author)For an Autonomous Vehicle (AV) to traverse safely in traffic, It is vital it can anticipate the behavior of surrounding traffic participants using motion prediction. Current motion prediction approaches can be categorized into object-centered and object-agnostic methods and are primarily based on deep learning. The former relies on a human...master thesis 2022
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Louwen, Anton (author)Radio frequency fingerprinting has been identified as a method to increase integrity in aircraft surveillance while retaining its openness. One way to uniquely determine transmitting devices is to distill the device its radio frequency (RF) fingerprint by looking at the physical features of the message signal it transmits. This physical layer...master thesis 2022