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Van der Laan, T.A. (author)The works [Volodymyr et al. Playing atari with deep reinforcement learning. arXiv preprint arXiv:1312.5602, 2013.] and [Volodymyr et al. Human-level control through deep reinforcement learning. Nature, 518(7540):529–533, 2015.] have demonstrated the power of combining deep neural networks with Watkins Q learning. They introduce deep Q networks ...master thesis 2015
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Nugroho, H. (author)Optical beamforming networks (OBFNs), which consist of many small and flat antennas, called phased array antennas (PAAs), can be tuned such that the signal beam from the airplanes can be steered towards a satellite. This was proposed as a alternative to the mechanically steered antenna, which has many disadvantages. The problem of tuning a large...master thesis 2015
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van Rosmalen, N.C. (author)To possess a computer algorithm that can perform the popular task of object localization with only weak supervision is valuable for numerous reasons. Often enough a certain localization task (e.g. bird localization) simply does not have properly annotated training data available. In this thesis a novel approach called Positive Class Localization...master thesis 2016
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Kathmann, Y. (author)This thesis aims to combine visual data and distance measurements from a Laser Range Finder (LRF) to recognise the presence of humans. The data from the LRF is used to find regions of interest in order to reduce the load on the visual data analysis. Deep learning convolutional neural networks have shown incredible results on visual recognition...master thesis 2017
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Goes, Sten (author)The millions of filter weights in Convolutional Neural Networks (CNNs), all have a well-defined and analytical expression for the partial derivative to the loss function. Therefor these weights can be learned from data with a technique called gradient descent optimization. While the filter weights have a well-defined derivative, the filter size...master thesis 2017
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Nijessen, Rik (author)Repository mining researchers have successfully applied machine learning in a variety of<br/>scenarios. However, the use of deep learning in repository mining tasks is still in its infancy.<br/>In this thesis, we describe the advantages and disadvantages of using deep learning in mining software repository research and demonstrate these by...master thesis 2017
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Kisantal, Máté (author)Safe navigation in a cluttered environment is a key capability for the autonomous operation of Micro Aerial Vehicles (MAVs). This work explores a (deep) Reinforcement Learning (RL) based approach for monocular vision based obstacle avoidance and goal directed navigation for MAVs in cluttered environments. We investigated this problem in the...master thesis 2018
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Ortiz Jimenez, Guillermo (author)In this era of data deluge, we are overwhelmed with massive volumes of extremely complex datasets. Data generated today is complex because it lacks a clear geometric structure, comes in great volumes, and it often contains information from multiple domains. In this thesis, we address these issues and propose two theoretical frameworks to handle...master thesis 2018
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Dritsas, Athanasios (author)In the last years, the popularity of video-on-demand services has been constantly increasing, especially for the young audiences who are more adept at using new technologies. Through those platforms, the viewers have access to a huge volume of movies at any moment that makes the viewing decision for most of them a very challenging task....master thesis 2019
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Zhou, Zequn (author)Urban areas are rapidly expanding in developing countries. One of goals of the United Nations Human Settlement Programme (UN-Habitat) is to understand and guide urban development for some developing regions.<br/>Currently, the approaches that UN-Habitat is using cost plenty of workforce, material, and time. Therefore, UN-Habitat is interested in...master thesis 2019
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Anand, Kanav (author)Deep learning is proving to be a useful tool in solving problems from various domains. Despite a rich research activity leading to numerous interesting deep learning models, recent large scale studies have shown that with hyperparameter optimization it is hard to distinguish these models based on their final performance. Hyperparameter...master thesis 2019
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Lengyel, Attila (author)This work investigates how prior knowledge from physics-based reflection models can be used to improve the performance of semantic segmentation models under an illumination-based domain shift. We implement various color invariants as a preprocessing step and find that CNNs trained on these color invariants get stuck in worse local minima...master thesis 2019
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Freiherr von der Goltz, Julian (author)Aircraft inspections after unexpected incidents, like lightning strikes, currently require a timeconsuming and costly inspection process, due to the small size of the lightning strike damages. Mainblades Inspections is working on an automated, drone-based solution, that scans the aircraft hull with a high-resolution camera. The objective of this...master thesis 2019
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Maan, Riya (author)Speech recognition systems can be found all around us. From personal assistants in mobile phones and smart speakers to robots, we use speech recognition systems everyday. However, communicating with them can be troublesome in noisy environments because they only use audio signals for speech recognition. This problem can be solved by using visual...master thesis 2019
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Jurasiński, Karol (author)Recently, deep generative models have been shown to achieve state-of-the-art performance on semi-supervised learning tasks. In particular, variational autoencoders have been adopted to use labeled data, which allowed the development of SSL models with the usage of deep neural networks. However, some of these models rely on ad-hoc loss additions...master thesis 2019
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Adank, Marloes (author)Objective: Recent studies have suggested an association between age-related hearing loss and cognitive decline. Yet, the underlying mechanism explaining this relation remains unknown. In this regard, several studies investigated gray matter (GM) differences in age-related hearing loss but presented inconsistent results regarding the association...master thesis 2019
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Dijkstra, Fokke (author)A variety of statistical methods are available to detect sudden changes, or breakpoints, in time series when used as multi-temporal change detection technique. However, these methods are unreliable in the presence of noise. Neural nets might detect breakpoints better. These deep learning models are able to generalize and optimize well, even in...master thesis 2020
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Davidse, Davy (author)This thesis discusses the application of deep learning to Coherent Fourier<br/>Scatterometry data in order to quickly and reliably detect nanoparticles on<br/>surfaces. An introduction to deep learning is followed by a review of the<br/>experimental setup and used software. After that, results are presented of<br/>classification accuracy tests...master thesis 2020
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Kaniouras, Pantelis (author)Road network maps facilitate a great number of applications in our everyday life. However, their automatic creation is a difficult task, and so far, published methodologies cannot provide reliable solutions. The common and most recent approach is to design a road detection algorithm from remote sensing imagery based on a Convolutional Neural...master thesis 2020
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Yin, Rukai (author)System Dynamics (SD) is an approach to study the nonlinear behaviour of complex systems over time. SD models provide a highlevel understanding of the system and aid in designing policies to achieve specific system behaviours. Conventional SD modelling requires an intensive amount of time, human resources and effort. Applying Machine Learning ...master thesis 2020