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Lende, Knut Roar (author)
Linear Parameter-Varying (LPV) systems can be used as a bridge to extend the well studied model based control methods of Linear Time-Invariant systems to certain nonlinear systems. Despite significant attention in literature over the last two decades, finding an efficient global state space identification algorithm remains an open problem....
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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van Engen, Femke (author)
Meditation is a contemplative practice that is believed to entail attentional and emotional regulation. One of the biggest challenges in developing personalized, accessible healthcare options with meditation is finding understandable features that signify whether someone is meditating. Specifically, there is no consensus on a feature resulting...
master thesis 2022
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Klaoudatos, Dimitrios (author)
This MSc thesis presents the development of a viewpoint optimization framework to face the problem of detecting occluded fruits in autonomous harvesting. A Deep Reinforcement Learning (DRL) algorithm is developed in order to train a robotic manipulator to navigate to occlusion-free viewpoints of the tomato-target. Two Convolutional Neural...
master thesis 2021
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de Almeida Nieto, Luis (author)
The scientific analysis of historical paintings has been traditionally restricted to the analysis of paint cross-section samples. This invasive method provides extensive information but is inherently limited in scope due to the extreme heterogeneity of paintings. In the last decade, non-invasive spot analyses and spectral imaging methods have...
master thesis 2020
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YANG, MINGHAO (author)
One-Shot Neural Architecture Search (NAS) is a promising method to significantly reduce search time without any separate training. It can be treated as a Network Compression problem on the architecture parameters from an overparameterized network. However, there are two issues associated with most one-shot NAS methods. First, dependencies...
master thesis 2019
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