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Daniel Noel, Alejandro (author)
Intelligent agents must pursue their goals in complex environments with partial information and often limited computational capacity. Reinforcement learning methods have achieved great success by creating agents that optimize engineered reward functions, but which often struggle to learn in sparse-reward environments, generally require many...
master thesis 2021
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Koffas, Stefanos (author)
Deep learning has made tremendous success in the past decade. As a result, it is becoming widely deployed in various safety and security-critical applications like autonomous driving, malware detection, fingerprint identification, and financial fraud detection. It was recently shown that deep neural networks are susceptible to multiple attacks...
master thesis 2021
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de Bruijne, Bas (author)
Ground based telescope imaging suffers from interference from the earth’s atmosphere. Fluctuations in the refractive index of the air delay incoming light randomly, resulting in blurred images. A deconvolution from wavefront sensing system is an adaptive optics system that measures the modes in which the light is corrupted (i.e. the wavefront)...
master thesis 2021
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Vogiatzis, Anastasios (author)
Everything around us is rapidly changing. Whole new blocks of buildings are built, huge infrastructural projects are constructed and so on. Hence, there is a need of a reliable and up-to-date inventory of the area and the objects of interest for mapping and monitoring assets and their changes. An answer of this upcoming need is an automated...
master thesis 2021
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Levenbach, Robert (author)
In this research, Dutch phoneme recognition (PR) is researched and improved. The last research on Dutch PR dates back to 1995. This research presents Dutch PR in modern daylight by researching state-of-the-art techniques found in research on other languages and implementing them on Dutch PR. The goal of this research is to find the current best...
master thesis 2021
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Dainelli, Filippo (author)
Extra-Tropical Cyclones (ETCs) are major storm system ruling and influencing the atmospheric structure at mid-latitudes. These events are usually characterized by strong winds and heavy precipitation and cause considerable storm surges with threatening wave systems for coastal regions. The possibility to simulate these storms or to increase the...
master thesis 2020
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Mattar, Avinash (author)
Passive acoustic sensing utilizes the ability of sound to travel beyond the line-of-sight to understand the surroundings. This provides an advantage over the currently used sensors in Intelligent Vehicles that can sense obstacles within their line-of-sight only. Recently, a localization based approach has been implemented to take advantage of...
master thesis 2020
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Meng, Fancong (author)
Localization is a problem of ’where we are’. Localization techniques help people understand their surrounding environment based on extracted position information in a geographic reference map. The development of global navigation satellite system (GNSS), light detection and ranging (LiDAR), computer vision (CV), etc., enables us to apply...
master thesis 2020
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Rijsdijk, Jorai (author)
Side-channel attacks (SCA), which use unintended leakage to retrieve a secret cryptographic key, have become more sophisticated over time. With the recent successes of machine learning (ML) and especially deep learning (DL) techniques against cryptographic implementations even in the presence of dedicated countermeasures, various methods have...
master thesis 2020
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Chen, Shaoqing (author)
Environmental sound identification and recognition aim to detect sound events within an audio clip. This technology is useful in many real-world applications such as security systems, smart vehicle navigation and surveillance of noise pollution, etc. Research on this topic has received increased attention in recent years. Performance is...
master thesis 2020
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Werner, Oliver (author)
In clinical practice, as a first approximation, the severity of an abnormality on an image is often determined by measuring its volume. Researchers often first segment this abnormality with a neural network trained by voxel-wise labels and thereafter extract the volume. Instead of this indirect two steps approach, we propose to train neural...
master thesis 2020
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Bonhof, Stefan (author)
Performing tasks in dynamic environments is still an open challenge in robotics. To be able to perform a task reliably in such scenarios, the state of the world has to be continuously monitored. In this context, most state-of-the-art perception methods focus on the recognition and classification of individual objects. However, these methods...
master thesis 2020
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Bhatnagar, Prernna (author)
Magnetic Resonance Imaging is a popular modality for brain imaging in present times. The quality of the images depends on the strength of the magnetic field. An MRI scanner with a magnetic field strength of 3 Tesla(T) is pre-dominantly used for clinical purposes. However, with the advancement in technology, and the need to image finer image...
master thesis 2020
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Choi, Yapkan (author)
Person re-identification based on appearance is challenging due to varying views and lighting conditions in different cameras, or when multiple persons wear similar clothing styles and color. Considering these challenges, gait patterns provide an alternative to appearance, as gait can be captured from a distance and at a low resolution. In this...
master thesis 2020
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Zia, Noor ul Sehr (author)
A good action proposal method should generate proposals with high recall and high temporal overlap with groundtruth. The quality of the proposals relies on the labeled data available during training. Obtaining labeled data for untrimmed videos is a time consuming, expensive and error-prone task. The labels obtained are also subjective and the...
master thesis 2020
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Pytel, Rafal (author)
Occlusion degrades the performance of human pose estimation. In this paper, we introduce targeted keypoint and body part occlusion attacks. The effects of the attacks are systematically analyzed on the best-performing methods. In addition, we propose occlusion specific data augmentation techniques against keypoint and part attacks. Our extensive...
master thesis 2020
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Soilis, P. (author)
Deep learning models have achieved state-of-the-art performance on several image classification tasks over the past years. Several studies claim to approach or even surpass human-levels of performance when using such models to classify images. However, these architectures are notoriously complex, thus making their interpretation a challenge....
master thesis 2020
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Mukherjee, A. (author)
The time taken to generate a super-resolution image and the quality of the final synthetic image depends on the performance of the localization algorithm which is used in the localization microscopy pipeline. The most precise and accurate algorithms are mostly iterative and they take a long time to generate the localization list while the faster...
master thesis 2020
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Sudharsan, S. (author)
Deep learning has enabled technologies that have been perceived complex or impossible a few years ago. Deep learning models can be used to solve several complex problem statements thereby making it a prominent field of research. With the advancements of Deep learning models, their application in domains have diversified. One prominent use-case...
master thesis 2020
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Smit, M. (author), Chen, Z. (author), Erbaşu, M.A. (author), Gaol, Y.A.L. (author), Li, X. (author)
With the constantly evolving range of applications for technology the quality and amount of data constantly increases as well. In this growing data environment, there is a constant search to provide more value to all data that is available for as little effort as possible. Our research tries to add such additional value by diving into the...
student report 2020
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