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Lelekas, Ioannis (author)Biological vision adopts a coarse-to-fine information processing pathway, from initial visual detection and binding of salient features of a visual scene, to the enhanced and preferential processing given relevant stimuli. On the contrary, CNNs employ a fine-to-coarse processing, moving from local, edge-detecting filters to more global ones...master thesis 2020
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Fris, Rein (author)Deep Reinforcement Learning (DRL) enables us to design controllers for complex tasks with a deep learning approach. It allows us to design controllers that are otherwise cumbersome to design with conventional control methodologies. Often, an objective for RL is binary in nature. However, exploring in environments with sparse rewards is a problem...master thesis 2020
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Geçmen, Dilan (author)Delft University of Technology (TU Delft), Leiden University Medical Center (LUMC), Pennsylvania State University (PSU) and Mbarara University of Science and Technology (MUST) have an ongoing collaboration to create an affordable, portable and simplified version of the magnetic resonance imaging (MRI) scan for the CURE children’s hospital to...master thesis 2020
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Hegeman, Rick (author)Combating air pollution has proven to be a difficult task for countries with rapidly developing economies. Poor air quality can be hazardous to people doing any outdoor activities. So being able to make accurate, short term air quality predictions can be very useful. However, making these predictions has proven to be quite difficult, since there...master thesis 2020
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Schönfeld, Mariette (author)Machine learning has been a computer sciences buzzword for years. The technology has a lot of potential and a huge number of applications that spoke to people with and without knowledge of computer sciences. Image, text and speech recognition, social profiling, computergames, everything seemed possible. Machine learning is not as much in the...bachelor thesis 2020
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de Bruin, T.D. (author)The arrival of intelligent, general-purpose robots that can learn to perform new tasks autonomously has been promised for a long time now. Deep reinforcement learning, which combines reinforcement learning with deep neural network function approximation, has the potential to enable robots to learn to perform a wide range of new tasks while...doctoral thesis 2020
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Erba, Alessandro (author), Taormina, R. (author), Galelli, Stefano (author), Pogliani, Marcello (author), Carminati, Michele (author), Zanero, Stefano (author), Tippenhauer, Nils Ole (author)Recently, reconstruction-based anomaly detection was proposed as an effective technique to detect attacks in dynamic industrial control networks. Unlike classical network anomaly detectors that observe the network traffic, reconstruction-based detectors operate on the measured sensor data, leveraging physical process models learned a priori....conference paper 2020
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Balado Frías, J. (author), Díaz-Vilarino, L. (author), Verbree, E. (author), Arias, P. (author)Indoor furniture is of great relevance to building occupants in everyday life. Furniture occupies space in the building, gives comfort, establishes order in rooms and locates services and activities. Furniture is not always static; the rooms can be reorganized according to the needs. Keeping the building models up to date with the current...journal article 2020
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Pérez-Dattari, Rodrigo (author), Celemin, Carlos (author), Ruiz-del-Solar, Javier (author), Kober, J. (author)Deep Reinforcement Learning (DRL) has become a powerful strategy to solve complex decision making problems based on Deep Neural Networks (DNNs). However, it is highly data demanding, so unfeasible in physical systems for most applications. In this work, we approach an alternative Interactive Machine Learning (IML) strategy for training DNN...conference paper 2020
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Perin, G. (author), Chmielewski, Łukasz (author), Batina, Lejla (author), Picek, S. (author)To mitigate side-channel attacks, real-world implementations of public-key cryptosystems adopt state-of-the-art countermeasures based on randomization of the private or ephemeral keys. Usually, for each private key operation, a “scalar blinding” is performed using 32 or 64 randomly generated bits. Nevertheless, horizontal attacks based on a...journal article 2020
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Tubbing, Rico (author)A side-channel attack (SCA) recovers secret data from a device by exploiting unintended physical leakages such as power consumption. In a profiled SCA, we assume an adversary has control over a target and copy device. Using the copy device the adversary learns a profile of the device. With the profile, the adversary exploits the measurements...master thesis 2019
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Voss, Sander (author)Spacecraft require high availability, autonomous operation, and a high degree of mission success. Spacecraft use sensors, such as star trackers and GPS, and actuators, such as reaction wheels, to reach and maintain a correct attitude and position. Failures in these components will have a significant negative impact on the success of the mission,...master thesis 2019
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van Hoek, Bob (author)Background: For both hospitals and patients it would be beneficial if the scan time of MR images could be reduced. At the moment, Compressed Sensing (CS) is introduced to reduce the scan time, however, new methods are developed such as a deep learning method, called the Recurrent Inference Machine (RIM). In this study the effect of...master thesis 2019
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Autar, Ravi (author)Person re-identification (re-ID) is a task that aims to associate the same people across different cameras. One of the many important problems a person re-ID system has to address in order to achieve good performance is the feature misalignment problem. Past research has attempted to address this problem by using attention networks, pose...master thesis 2019
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Pop, Marius (author)Security has become ever more important in today's quickly growing digital world as the number of digital assets has quickly grown. Our thesis focuses on devices that compute a secure cryptographic operation such that information can be communicated or authenticated. The attack vector utilized is known as Profiled Side-Channel Analysis (SCA)...master thesis 2019
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Kapadia, Husain (author)Listening in noise is a challenging problem that affects the hearing capability of not only normal hearing but especially hearing impaired people. Since the last four decades, enhancing the quality and intelligibility of noise corrupted speech by reducing the effect of noise has been addressed using statistical signal processing techniques as...master thesis 2019
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Li, Xin (author)Visual context plays a key role in many computer vision tasks, and performance of eye/gaze-tracking methods also benefit from it. However, the size of contextual information (e.g. full face image) is very large w.r.t the primary input i.e. cropped image of the eye. This adds large computational costs to the algorithm and makes it inefficient,...master thesis 2019
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Graur, Dan (author)Given the increasing popularity of Machine Learning, and the ever increasing need to solve larger and more complex learning challenges, it is unsurprising that numerous distributed learning strategies have been brought forward in recent years, along with many large scale Machine Learning frameworks. It is however unclear how well these...master thesis 2019
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Riegger, Franzi (author)Quantitative analysis of material microstructure is a well-known method to derive chemical and physical properties of a sample. This includes the segmentation of e.g. Light Optical Microscopy or Scanning Electron Microscopy images where each pixel is assigned to a material. Since some phases such as the γ-γ’ structure in nickelbased superalloys...master thesis 2019
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Wang, Yizhou (author)In the past few years, convolutional neural networks (CNNs) have been widely utilized and shown state-of-the-art performances on computer vision tasks. However, CNN based approaches usually require a large amount of storage, run-time memory, as well as computation power in both training and inference time, which are usually used on GPU based...master thesis 2019