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Suryanarayana, Gowri (author), Lago, Jesus (author), Geysen, Davy (author), Aleksiejuk, Piotr (author), Johansson, Christian (author)Recent research has seen several forecasting methods being applied for heat load forecasting of district heating networks. This paper presents two methods that gain significant improvements compared to the previous works. First, an automated way of handling non-linear dependencies in linear models is presented. In this context, the paper...journal article 2018
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Lago, Jesus (author), De Brabandere, Karel (author), De Ridder, Fjo (author), De Schutter, B.H.K. (author)Due to the increasing integration of solar power into the electrical grid, forecasting short-term solar irradiance has become key for many applications, e.g. operational planning, power purchases, reserve activation, etc. In this context, as solar generators are geographically dispersed and ground measurements are not always easy to obtain,...journal article 2018
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Buşoniu, Lucian (author), de Bruin, T.D. (author), Tolić, Domagoj (author), Kober, J. (author), Palunko, Ivana (author)Reinforcement learning (RL) offers powerful algorithms to search for optimal controllers of systems with nonlinear, possibly stochastic dynamics that are unknown or highly uncertain. This review mainly covers artificial-intelligence approaches to RL, from the viewpoint of the control engineer. We explain how approximate representations of the...review 2018
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de Bruin, T.D. (author), Kober, J. (author), Tuyls, K.P. (author), Babuska, R. (author)Experience replay is a technique that allows off-policy reinforcement-learning methods to reuse past experiences. The stability and speed of convergence of reinforcement learning, as well as the eventual performance of the learned policy, are strongly dependent on the experiences being replayed. Which experiences are replayed depends on two...journal article 2018
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Lago, Jesus (author), De Ridder, Fjo (author), De Schutter, B.H.K. (author)In this paper, a novel modeling framework for forecasting electricity prices is proposed. While many predictive models have been already proposed to perform this task, the area of deep learning algorithms remains yet unexplored. To fill this scientific gap, we propose four different deep learning models for predicting electricity prices and...journal article 2018
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Sorgedrager, Riemer (author)This study focuses on automated malaria diagnosis in low quality blood smear images, captured by a low-cost smartphone based microscope system. The aim is to localize and classify the healthy and infected erythrocytes (red blood cells) in order to evaluate the parasitaemia in an infected blood smear. Due to the lower quality of the smartphone...master thesis 2018
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Xie, Yu (author)Facing the severe air pollution phenomenon in urban areas and the subsequent low visibility event in airports, it is urgent to conduct air quality and visibility predictions to better reflect their changing trends. However, the variations of PM2.5 and visibility involve complicated physical and chemical processes, which make their accurate...master thesis 2018
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Dijkstra, Timo Johannes (author)The versatility of the hands is revealed in its movements, but often not noticed before trauma occurs. Joint range of motion is used as a measure to follow the progress of diseases. A digital workflow for 3D data in medical appliances is envisioned for years.<br/>The aim of this research is to develop a method that reliably and reproducability...master thesis 2018
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van Wijnen, Kimberlin (author)Perivascular spaces (PVS) visible on MRI are currently emerging as an important potential neuroimaging marker for several pathologies in the brain like Alzheimer’s disease and cerebral small vessel disease. PVS are fluid-filled spaces surrounding vessels as they enter the brain. Although PVS are normally not noticeable on MRI scans acquired at...master thesis 2018
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Gama, F. (author), Marques, Antonio G. (author), Leus, G.J.T. (author), Ribeiro, Alejandro (author)Two architectures that generalize convolutional neural networks (CNNs) for the processing of signals supported on graphs are introduced. We start with the selection graph neural network (GNN), which replaces linear time invariant filters with linear shift invariant graph filters to generate convolutional features and reinterprets pooling as a...journal article 2019
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Paltrinieri, Nicola (author), Comfort, Louise (author), Reniers, G.L.L.M.E. (author)Risk assessment has a primary role in safety-critical industries. However, it faces a series of overall challenges, partially related to technology advancements and increasing needs. There is currently a call for continuous risk assessment, improvement in learning past lessons and definition of techniques to process relevant data, which are...journal article 2019
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Mozaffar, M. (author), Bostanabad, R. (author), Chen, W. (author), Ehmann, K. (author), Cao, J. (author), Bessa, M.A. (author)Plasticity theory aims at describing the yield loci and work hardening of a material under general deformation states. Most of its complexity arises from the nontrivial dependence of the yield loci on the complete strain history of a material and its microstructure. This motivated 3 ingenious simplifications that underpinned a century of...journal article 2019
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Dubost, Florian (author), Yilmaz, Pinar (author), Adams, Hieab (author), Bortsova, Gerda (author), Ikram, M. Arfan (author), Niessen, W.J. (author), Vernooij, Meike (author), de Bruijne, Marleen (author)Enlarged perivascular spaces (PVS) are structural brain changes visible in MRI, are common in aging, and are considered a reflection of cerebral small vessel disease. As such, assessing the burden of PVS has promise as a brain imaging marker. Visual and manual scoring of PVS is a tedious and observer-dependent task. Automated methods would...journal article 2019
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Gama, F. (author), Marques, Antonio G. (author), Leus, G.J.T. (author), Ribeiro, Alejandro (author)In this ongoing work, we describe several architectures that generalize convolutional neural networks (CNNs) to process signals supported on graphs. The general idea of the replace time invariant filters with graph filters to generate convolutional features and to replace pooling with sampling schemes for graph signals. The different...conference paper 2019
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Gudi, A.A. (author), Bittner, M. (author), Lochmans, Roelof (author), van Gemert, J.C. (author)Remote photo-plethysmography (rPPG) uses a remotely placed camera to estimating a person's heart rate (HR). Similar to how heart rate can provide useful information about a person's vital signs, insights about the underlying physio/psychological conditions can be obtained from heart rate variability (HRV). HRV is a measure of the fine...conference paper 2019
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Ghavamian, F. (author), Simone, A. (author)FE<sup>2</sup> multiscale simulations of history-dependent materials are accelerated by means of a recurrent neural network (RNN) surrogate for the history-dependent micro level response. We propose a simple strategy to efficiently collect stress–strain data from the micro model, and we modify the RNN model such that it resembles a nonlinear...journal article 2019
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Brand, Patrick (author)Recent advances in Artificial Intelligence and Computer Vision have been showed to be promising for automated land use classification of remotely sensed data. However, current state-of-the-art per-pixel segmentation networks fail to accurately capture geometrical and topological properties on land use segmentation, as these methods have...master thesis 2019
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Resink, Tim (author)To be able to understand the dynamic driving environment, an autonomous vehicle needs to predict the mo- tion of other traffic participants in the driving scene. Motion prediction can be done based on experience and recently observed series of past events, and entails reasoning about probable outcomes with these past ob- servations. Aspects that...master thesis 2019
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Al-Rahbi, Mohammed (author)Human Activity Recognition (HAR) is a key enabler of various applications, including smart homes, health care, Internet of Things (IoT), and virtual reality games. A large number of HAR systems are based on wearable sensors and computer vision. However, a challenge that has emerged in the last few years entails recognizing human activities using...master thesis 2019
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Li, Mingxi (author)Neural networks have achieved great success in many difficult learning tasks like image classification, speech recognition and natural language processing. However, neural architectures are hard to design, which requires lots of knowledge and time of human experts. Therefore, there has been a growing interest in automating the process of designing...master thesis 2019