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Cuperman, Rafael (author), Jansen, K.M.B. (author), Ciszewski, M.G. (author)Action statistics in sports, such as the number of sprints and jumps, along with the details of the corresponding locomotor actions, are of high interest to coaches and players, as well as medical staff. Current video-based systems have the disadvantage that they are costly and not easily transportable to new locations. In this study, we...journal article 2022
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Mostafavi, F. (author), Tahsildoost, Mohammad (author), Zomorodian, Zahra Sadat (author), Shahrestani, Seyed Shayan (author)Purpose: In this study, a novel framework based on deep learning models is presented to assess energy and environmental performance of a given building space layout, facilitating the decision-making process at the early-stage design. Design/methodology/approach: A methodology using an image-based deep learning model called pix2pix is proposed...journal article 2022
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Li, Fang (author), Li, Xueyuan (author), Liu, Qi (author), Li, Z. (author)Pedestrian detection is an important branch of computer vision, and it has important applications in the fields of autonomous driving, artificial intelligence and video surveillance.With the rapid development of deep learning and the proposal of large-scale datasets, pedestrian detection has reached a new stage and achieves better performance...journal article 2022
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Smirnova, Alisa (author), Yang, J. (author), Yang, Dingqi (author), Cudre-Mauroux, Philippe (author)Noisy labels represent one of the key issues in supervised machine learning. Existing work for label noise reduction mainly takes a probabilistic approach that infers true labels from data distributions in low-level feature spaces. Such an approach is not only limited by its capability to learn high-quality data representations, but also by...journal article 2022
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Shengren, H. (author), Salazar, Edgar Mauricio (author), Vergara Barrios, P.P. (author), Palensky, P. (author)Taking advantage of their data-driven and model-free features, Deep Reinforcement Learning (DRL) algorithms have the potential to deal with the increasing level of uncertainty due to the introduction of renewable-based generation. To deal simultaneously with the energy systems’ operational cost and technical constraints (e.g, generation-demand...conference paper 2022
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Viana, Paula (author), Andrade, Maria Teresa (author), Carvalho, Pedro (author), Vilaça, Luis (author), Teixeira, Inês N. (author), Costa, Tiago (author), Jonker, P.P. (author)Applying machine learning (ML), and especially deep learning, to understand visual content is becoming common practice in many application areas. However, little attention has been given to its use within the multimedia creative domain. It is true that ML is already popular for content creation, but the progress achieved so far addresses...journal article 2022
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Mohammadpourfard, Mostafa (author), Weng, Yang (author), Khalili, Abdullah (author), Genc, Istemihan (author), Shefaei, A. (author), Mohammadi-Ivatloo, Behnam (author)The expansion of power systems over large geographical areas renders centralized processing inefficient. Therefore, the distributed operation is increasingly adopted. This work introduces a new type of attack against distributed state estimation of power systems, which operates on inter-area boundary buses. We show that the developed attack...journal article 2022
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Merkx, D.G.M. (author), Scholten, Sebastiaan (author), Frank, Stefan L. (author), Ernestus, Mirjam (author), Scharenborg, O.E. (author)Many computational models of speech recognition assume that the set of target words is already given. This implies that these models learn to recognise speech in a biologically unrealistic manner, i.e. with prior lexical knowledge and explicit supervision. In contrast, visually grounded speech models learn to recognise speech without prior...journal article 2022
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Chaudhary, Shivam (author), Pandey, Pankaj (author), Miyapuram, Krishna Prasad (author), Lomas, J.D. (author)In the modern world, it is easy to get lost in thought, partly because of the vast knowledge available at our fingertips via smartphones that divide our cognitive resources and partly because of our intrinsic thoughts. In this work, we aim to find the differences in the neural signatures of mind-wandering and meditation that are common across...conference paper 2022
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Kerkhof, Maikel (author), Wu, L. (author), Perin, G. (author), Picek, S. (author)The deep learning-based side-channel analysis represents one of the most powerful side-channel attack approaches. Thanks to its capability in dealing with raw features and countermeasures, it becomes the de facto standard approach for the SCA community. The recent works significantly improved the deep learning-based attacks from various...conference paper 2022
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Mody, Prerak (author), Chaves-de-Plaza, Nicolas F. (author), Hildebrandt, K.A. (author), Staring, M. (author)Bayesian Neural Nets (BNN) are increasingly used for robust organ auto-contouring. Uncertainty heatmaps extracted from BNNs have been shown to correspond to inaccurate regions. To help speed up the mandatory quality assessment (QA) of contours in radiotherapy, these heatmaps could be used as stimuli to direct visual attention of clinicians to...conference paper 2022
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Rezaeezade, A. (author), Perin, G. (author), Picek, S. (author)Profiling side-channel analysis allows evaluators to estimate the worst-case security of a target. When security evaluations relax the assumptions about the adversary’s knowledge, profiling models may easily be sub-optimal due to the inability to extract the most informative points of interest from the side-channel measurements. When used for...conference paper 2022
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Andringa, S.P.E. (author), Yorke-Smith, N. (author)Simulation–optimization is often used in enterprise decision-making processes, both operational and tactical. This paper shows how an intuitive mapping from descriptive problem to optimization model can be realized with Constraint Programming (CP). It shows how a CP model can be constructed given a simulation model and a set of business goals...conference paper 2022
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Rijsdijk, Jorai (author), Wu, L. (author), Perin, G. (author)Deep learning-based side-channel attacks are capable of breaking targets protected with countermeasures. The constant progress in the last few years makes the attacks more powerful, requiring fewer traces to break a target. Unfortunately, to protect against such attacks, we still rely solely on methods developed to protect against generic...conference paper 2022
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Danaei, Deniz (author)<br/>The fight against the illegal hunting of African wildlife is a never-ending process. In order to preserve animal habitats and save them from extinction, many national parks utilize surveilling solutions to prevent, detect and locate intruders. One strategy to detect and locate the illegal hunters or so-called \textit{poachers} is to detect...master thesis 2021
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Zijta, Marcella (author)Hydrocephalus is a disease where an excess of cerebrospinal fluid (CSF) is built up in the brain. It affects approximately 180.000 infants per year in sub-Saharan Africa. Magnetic resonance imaging (MRI) is an advantageous imaging method to diagnose hydrocephalus and examine the amount of fluid in the brain for treatment. Unfortunately, in sub...master thesis 2021
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Baas, Berend (author)Existing work in shape editing applications using deep learning has primarily focused on shape interpolation.<br/>We propose a pair of techniques that utilize the latent space of deformation networks to provide control schemes for semantic shape editing applications.<br/><br/>The first technique presented utilizes linear directions as...master thesis 2021
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Suryanarayanan, Surya Narayanan (author)Inverse design with topology optimization has followed the same computational<br/>graph for decades. The unknown material density is distributed within a domain,<br/>a computational analysis predicts the response of that design and its derivative<br/>with respect to the unknown, and this information is used by a chosen gradient<br/>based...master thesis 2021
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Arunmoli, Karthik Arvind (author)Learning from demonstration is a technique where the robot learns directly from humans. It can be beneficial to learn from humans directly because humans can easily demonstrate complex behaviors without being experts in demonstrating required tasks. However, it can be challenging to gather large amounts of data from humans because humans often...master thesis 2021
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Wiersma, Mark (author)Automated bin-picking is a difficult task that requires solving multiple robotic vision problems including object detection and grasp proposal generation. Current methods use deep learning to approach each of the vision problems of bin-picking separately with the main focus on generating the grasp proposals. For grasp proposal generation, neural...master thesis 2021