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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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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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Wang, H. (author), Nunez, Alfredo (author)The catenary insulator maintains electrical insulation between catenary and ground. Its defects may happen due to the long-term impact from vehicle and environment. At present, the research of defect detection for catenary insulator faces several challenges. 1) Localization accuracy is low, which causes the localized object to be incomplete or...journal article 2020
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Jiang, Shijie (author), Zheng, Yi (author), Solomatine, D.P. (author)Modeling dynamic geophysical phenomena is at the core of Earth and environmental studies. The geoscientific community relying mainly on physical representations may want to consider much deeper adoption of artificial intelligence (AI) instruments in the context of AI's global success and emergence of big Earth data. A new perspective of using...journal article 2020
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Roy, Devjeet (author), Zhang, Ziyi (author), Ma, Maggie (author), Arnaoudova, Venera (author), Panichella, A. (author), Panichella, Sebastiano (author), Gonzalez, Danielle (author), Mirakhorli, Mehdi (author)Automated test case generation tools have been successfully proposed to reduce the amount of human and infrastructure resources required to write and run test cases. However, recent studies demonstrate that the readability of generated tests is very limited due to (i) uninformative identifiers and (ii) lack of proper documentation. Prior...conference paper 2020
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Jia, Mu (author), Li, Shaoxuan (author), Le Kernec, Julien (author), Yang, Shufan (author), Fioranelli, F. (author), Romain, Olivier (author)As the number of older adults increases worldwide, new paradigms for indoor activity monitoring are required to keep people living at home independently longer. Radar-based human activity recognition has been identified as a sensing modality of choice because it is privacy-preserving and does not require end-users compliance or manipulation. In...conference paper 2020
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Basu, S. (author), Watson, S.J. (author), Lacoa Arends, Eric (author), Cheneka, B.R. (author)A hybrid neural network model, comprising of a convolutional neural network and a multilayer perceptron network, has been developed for day-ahead forecasting of regional scale wind power production. This model requires operational weather forecasts as input and also has the capability to ingest data from ensemble forecasts. Even though the...conference paper 2020
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Papanastasiou, V. S. (author), Trommel, R. P. (author), Harmanny, R. I.A. (author), Yarovoy, Alexander (author)For the first time identification of human individuals using micro-Doppler (m-D) features measured at X-band has been demonstrated. Deep Convolutional Neural Networks (DCNNs) have been used to perform classification. Inspection and visualization of the classification results were performed using Uniform Manifold Approximation and Projection ...conference paper 2021
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Guo, Rui (author), Weingärtner, S.D. (author), Šiuryté, P. (author), T. Stoeck, Christian (author), Füetterer, Maximilian (author), E. Campbell-Washburn, Adrienne (author), Suinesiaputra, Avan (author), Jerosch-Herold, Michael (author), Nezafat, Reza (author)Cardiovascular disease is the leading cause of death and a significant contributor of health care costs. Noninvasive imaging plays an essential role in the management of patients with cardiovascular disease. Cardiac magnetic resonance (MR) can noninvasively assess heart and vascular abnormalities, including biventricular structure/function,...review 2021
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Peschl, M. (author)We propose a deep reinforcement learning algorithm that employs an adversarial training strategy for adhering to implicit human norms alongside optimizing for a narrow goal objective. Previous methods which incorporate human values into reinforcement learning algorithms either scale poorly or assume hand-crafted state features. Our algorithm...conference paper 2021
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Koolstra, Kirsten (author), Remis, R.F. (author)Purpose: To learn a preconditioner that accelerates parallel imaging (PI) and compressed sensing (CS) reconstructions. Methods: A convolutional neural network (CNN) with residual connections was used to train a preconditioning operator. Training and validation data were simulated using 50% brain images and 50% white Gaussian noise images....journal article 2021
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Arapi, Visar (author), Della Santina, C. (author), Averta, Giuseppe (author), Bicchi, Antonio (author), Bianchi, Matteo (author)In recent years, the spread of data-driven approaches for robotic grasp synthesis has come with the increasing need for reliable datasets, which can be built e.g. through video labelling. To this goal, it is important to define suitable rules to characterize the main human grasp types, for easily identifying them in video streams. In this...journal article 2021
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Myers, N.J. (author), Kwon, Hyukjoon (author), Ding, Yacong (author), Song, Kee-Bong (author)In this paper, we propose a learning-aided signal processing solution for channel estimation in 5G new radio (NR). Channel estimation is an important algorithm for baseband modem design. In 5G NR, estimating the channel is challenging due to two reasons. First, the pilot signals are transmitted over a small fraction of the available time...conference paper 2021
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van der Heijden, T.J.T. (author), Lago, Jesus (author), Palensky, P. (author), Abraham, E. (author)In this manuscript we explore European feature importance in Day Ahead Market (DAM) price forecasting models, and show that model performance can deteriorate when too many features are included due to over-fitting. We propose a greedy algorithm to search over candidate countries for European features to be used in a DAM price forecasting model,...journal article 2021
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Widyaningrum, E. (author)A base map provides essential geospatial information for applications such as urban planning, intelligent transportation systems, and disaster management. Buildings and roads are the main ingredients of a base map and are represented by polygons. Unfortunately, manually delineating their boundaries from remote sensing data is time consuming and...doctoral thesis 2021
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Ghavamian, F. (author)We study the acceleration of the finite element method (FEM) simulations using machine learning (ML) models. Specifically, we replace computationally expensive (parts of) FEM models with efficient ML surrogates. We develop three methods to speed up FEM simulations. The primary difference between these models is their degree of intrusion into the...doctoral thesis 2021
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Ilioudi, A. (author), Dabiri, A. (author), Wolf, B.J. (author), De Schutter, B.H.K. (author)Deep learning has enabled the rapid expansion of computer vision tasks from image frames to video segments. This paper focuses on the review of the latest research in the field of computer vision tasks in general and on object localization and identification of their associated pixels in video frames in particular. After performing a systematic...journal article 2022
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Yin, Zhao (author), Geraedts, Victor Jacobus (author), Wang, Z. (author), Contarino, Maria Fiorella (author), Dibeklioglu, H. (author), van Gemert, J.C. (author)Parkinson's disease (PD) diagnosis is based on clinical criteria, i.e., bradykinesia, rest tremor, rigidity, etc. Assessment of the severity of PD symptoms with clinical rating scales, however, is subject to inter-rater variability. In this paper, we propose a deep learning based automatic PD diagnosis method using videos to assist the...journal article 2022