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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 ...journal article 2015
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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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Bessa, M.A. (author), Głowacki, Piotr (author), Houlder, Michael (author)Designing future-proof materials goes beyond a quest for the best. The next generation of materials needs to be adaptive, multipurpose, and tunable. This is not possible by following the traditional experimentally guided trial-and-error process, as this limits the search for untapped regions of the solution space. Here, a computational data...journal article 2019
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Baptista Ríos, M. (author), Lopez-Sastre, Roberto J. (author), Caba Heilbron, Fabian (author), van Gemert, J.C. (author), Acevedo-Rodriguez, F. Javier (author), Maldonado-Bascon, Saturnino (author)The Online Action Detection (OAD) problem needs to be revisited. Unlike traditional offline action detection approaches, where the evaluation metrics are clear and well established, in the OAD setting we find very few works and no consensus on the evaluation protocols to be used. In this work we propose to rethink the OAD scenario, clearly...journal article 2019
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Ewald, Vincentius (author), Groves, R.M. (author), Benedictus, R. (author)In our previous work, we demonstrated how to use inductive bias to infuse a convolutional neural network (CNN) with domain knowledge from fatigue analysis for aircraft visual NDE. We extend this concept to SHM and therefore in this paper, we present a novel framework called DeepSHM which involves data augmentation of captured sensor signals...conference paper 2019
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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