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Zhu, Jianfeng (author), Sui, Lichun (author), Zang, Y. (author), Zheng, He (author), Jiang, Wei (author), Zhong, Mianqing (author), Ma, Fei (author)
In various applications of airborne laser scanning (ALS), the classification of the point cloud is a basic and key step. It requires assigning category labels to each point, such as ground, building or vegetation. Convolutional neural networks have achieved great success in image classification and semantic segmentation, but they cannot be...
journal article 2021
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Thangavel, Prasanth (author), Thomas, John (author), Peh, Wei Yan (author), Jing, Jin (author), Yuvaraj, Rajamanickam (author), Cash, Sydney S. (author), Chaudhari, Rima (author), Saini, Vinay (author), Dauwels, J.H.G. (author)
Epilepsy diagnosis based on Interictal Epileptiform Discharges (IEDs) in scalp electroencephalograms (EEGs) is laborious and often subjective. Therefore, it is necessary to build an effective IED detector and an automatic method to classify IED-free versus IED EEGs. In this study, we evaluate features that may provide reliable IED detection...
journal article 2021
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van Stiphout, J.A. (author), Driessen, J. (author), Koetzier, L.R. (author), Ruules, L.B. (author), Willemink, Martin (author), Heemskerk, Jan W.T. (author), van der Molen, Aart J. (author)
Objective: To determine the difference in CT values and image quality of abdominal CT images reconstructed by filtered back-projection (FBP), hybrid iterative reconstruction (IR), and deep learning reconstruction (DLR). Methods: PubMed and Embase were systematically searched for articles regarding CT densitometry in the abdomen and the image...
journal article 2021
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Tian, Jinyan (author), Wang, Le (author), Yin, Dameng (author), Li, Xiaojuan (author), Diao, Chunyuan (author), Gong, Huili (author), Shi, Chen (author), Menenti, M. (author), Ge, Yong (author)
Invasive Spartina alterniflora (S. alterniflora), a native riparian species in the U.S. Gulf of Mexico, has led to serious degradation to the ecosystem and biodiversity as well as economic losses since it was introduced to China in 1979. Although multi-temporal remote sensing offers unique capability to monitor S. alterniflora over large...
journal article 2020
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Castillo, Jose M.T. (author), Arif, Muhammad (author), Niessen, W.J. (author), Schoots, Ivo G. (author), Veenland, J.F. (author)
Significant prostate carcinoma (sPCa) classification based on MRI using radiomics or deep learning approaches has gained much interest, due to the potential application in assisting in clinical decision-making. Objective: To systematically review the literature (i) to determine which algorithms are most frequently used for sPCa classification...
journal article 2020
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Wu, L. (author), Ribera, Gerard (author), Beringuier-Boher, Noemie (author), Picek, S. (author)
Semi-invasive fault injection attacks are powerful techniques well-known by attackers and secure embedded system designers. When performing such attacks, the selection of the fault injection parameters is of utmost importance and usually based on the experience of the attacker. Surprisingly, there exists no formal and general approach to...
conference paper 2020
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Dubost, Florian (author), Adams, Hieab (author), Yilmaz, Pinar (author), Bortsova, Gerda (author), Tulder, Gijs van (author), Ikram, M. Arfan (author), Niessen, W.J. (author), Vernooij, Meike W. (author), Bruijne, Marleen de (author)
Finding automatically multiple lesions in large images is a common problem in medical image analysis. Solving this problem can be challenging if, during optimization, the automated method cannot access information about the location of the lesions nor is given single examples of the lesions. We propose a new weakly supervised detection method...
journal article 2020
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Sapountzoglou, Nikolaos (author), Lago, Jesus (author), De Schutter, B.H.K. (author), Raison, Bertrand (author)
Power outages in electrical grids can have very negative economic and societal impacts rendering fault diagnosis paramount to their secure and reliable operation. In this paper, deep neural networks are proposed for fault detection and location in low-voltage smart distribution grids. Due to its key properties, the proposed method solves some...
journal article 2020
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Rahman, Muhammad Fazalul (author), Murukannaiah, P.K. (author), Sharma, Naveen (author)
Vacant lots are municipally-owned land parcels which were acquired post-abandonment or due to tax foreclosures. With time, failure to sell or find alternate uses for vacant lots results in them causing adverse effects on the health and safety of residents, and cost the city both directly and indirectly. Although existing research has tried to...
conference paper 2020
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Cao, Wen-Jun (author)
The train wheel flat is one of the most common damages in the railway system. It occurs when a wheel locks up while the train is moving. The early detection of wheel-flat severity is crucial for passenger comfort and the safety of the railway operation. However, it is still challenging to quantify the properties of wheel flats (e.g., sizes)...
conference paper 2020
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Wu, L. (author), Picek, S. (author)
In the profiled side-channel analysis, deep learning-based techniques proved to be very successful even when attacking targets protected with countermeasures. Still, there is no guarantee that deep learning attacks will always succeed. Various countermeasures make attacks significantly more complex, and such countermeasures can be further...
journal article 2020
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Weissbart, L.J.A. (author), Chmielewski, Łukasz (author), Picek, S. (author), Batina, Lejla (author)
Profiling attacks, especially those based on machine learning, proved to be very successful techniques in recent years when considering the side-channel analysis of symmetric-key crypto implementations. At the same time, the results for implementations of asymmetric-key cryptosystems are very sparse. This paper considers several machine learning...
journal article 2020
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Bonsignorio, Fabio (author), Hsu, David (author), Johnson-Roberson, Matthew (author), Kober, J. (author)
Deep learning has gone through massive growth in recent years. In many fields—computer vision, speech recognition, machine translation, game playing, and others—deep learning has brought unprecedented progress and become the method of choice. Will the same happen in robotics and automation? In a sense, it is already happening. Today, deep...
contribution to periodical 2020
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de Bruin, T.D. (author), Kober, J. (author), Tuyls, Karl (author), Babuska, R. (author)
Deep reinforcement learning makes it possible to train control policies that map high-dimensional observations to actions. These methods typically use gradient-based optimization techniques to enable relatively efficient learning, but are notoriously sensitive to hyperparameter choices and do not have good convergence properties. Gradient...
journal article 2020
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Pezzotti, Nicola (author), Yousefi, Sahar (author), Elmahdy, Mohamed S. (author), van Gemert, Jeroen Hendrikus Fransiscus (author), Schuelke, Christophe (author), Doneva, Mariya (author), Nielsen, Tim (author), Lelieveldt, B.P.F. (author), Staring, M. (author)
Adaptive intelligence aims at empowering machine learning techniques with the additional use of domain knowledge. In this work, we present the application of adaptive intelligence to accelerate MR acquisition. Starting from undersampled k-space data, an iterative learning-based reconstruction scheme inspired by compressed sensing theory is...
journal article 2020
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Ma, Hua (author), Smal, I.V. (author), Daemen, Joost (author), Walsum, Theo van (author)
Percutaneous coronary intervention (PCI) is typically performed with image guidance using X-ray angiograms in which coronary arteries are opacified with X-ray opaque contrast agents. Interventional cardiologists typically navigate instruments using non-contrast-enhanced fluoroscopic images, since higher use of contrast agents increases the...
journal article 2020
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Guédon, Annetje C.P. (author), Meij, S.E.P. (author), Osman, Karim N.M.M.H. (author), Kloosterman, Helena A. (author), van Stralen, Karlijn J. (author), Grimbergen, Matthijs C.M. (author), Eijsbouts, Quirijn A.J. (author), van den Dobbelsteen, J.J. (author), Twinanda, Andru P. (author)
perating room planning is a complex task as pre-operative estimations of procedure duration have a limited accuracy. This is due to large variations in the course of procedures. Therefore, information about the progress of procedures is essential to adapt the daily operating room schedule accordingly. This information should ideally be...
journal article 2020
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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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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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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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