Searched for: subject%3A%22convolutional%255C%2Bneural%255C%2Bnetwork%22
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Zhu, B. (author)
In recent years, the accuracy of Deep Neural Networks (DNNs) has improved significantly because of three main factors: the availability of massive amounts training data, the introduction of powerful low-cost computational resources, and the development of complex deep learning models. The cloud can provide powerful computational resources to...
doctoral thesis 2021
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Chen, Y. (author)
Single-photon emission computed tomography (SPECT) is a well-established nuclear imaging modality for studying functional and pathological properties of the brain. Conventional general purpose SPECT systems typically offer a spatial resolution of about 10 mm with a sensitivity of 0.01-0.02%. A few dedicated brain SPECT scanners have been...
doctoral thesis 2021
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Isufi, E. (author), Pocchiari, Matteo (author), Hanjalic, A. (author)
Graph convolutions, in both their linear and neural network forms, have reached state-of-the-art accuracy on recommender system (RecSys) benchmarks. However, recommendation accuracy is tied with diversity in a delicate trade-off and the potential of graph convolutions to improve the latter is unexplored. Here, we develop a model that learns...
journal article 2021
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Pasqualetto Cassinis, L. (author), Fonod, R. (author), Gill, E.K.A. (author), Ahrns, Ingo (author), Gil-Fernández, Jesús (author)
The relative pose estimation of an inactive spacecraft by an active servicer spacecraft is a critical task in the design of current and planned space missions, due to its relevance for close-proximity operations, such as In-Orbit Servicing and Active Debris Removal. This paper introduces a novel framework to enable robust monocular pose...
journal article 2021
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Ballan, Luca (author), Strafforello, O. (author), Schutte, Klamer (author)
Long-Term activities involve humans performing complex, minutes-long actions. Differently than in traditional action recognition, complex activities are normally composed of a set of sub-actions, that can appear in different order, duration, and quantity. These aspects introduce a large intra-class variability, that can be hard to model. Our...
conference paper 2021
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Xiao, C. (author), Leeuwenburgh, O. (author), Lin, H.X. (author), Heemink, A.W. (author)
Imaging-type monitoring techniques are used in monitoring dynamic processes in many domains, including medicine, engineering, and geophysics. This paper aims to propose an efficient workflow for application of such data for the conditioning of simulation models. Such applications are very common in e.g. the geosciences, where large-scale...
journal article 2021
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Wijnker, D.C. (author), van Dijk, Tom (author), Snellen, M. (author), de Croon, G.C.H.E. (author), de Wagter, C. (author)
To investigate how an unmanned air vehicle can detect manned aircraft with a single microphone, an audio data set is created in which unmanned air vehicle ego-sound and recorded aircraft sound are mixed together. A convolutional neural network is used to perform air traffic detection. Due to restrictions on flying unmanned air vehicles close to...
journal article 2021
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Sokooti, Hessam (author), Yousefi, Sahar (author), Elmahdy, Mohamed S. (author), Lelieveldt, B.P.F. (author), Staring, M. (author)
In this paper we propose a supervised method to predict registration misalignment using convolutional neural networks (CNNs). This task is casted to a classification problem with multiple classes of misalignment: 'correct' 0-3 mm, 'poor' 3-6 mm and 'wrong' over 6 mm. Rather than a direct prediction, we propose a hierarchical approach, where...
journal article 2021
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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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Bron, Esther E. (author), Klein, Stefan (author), Papma, Janne M. (author), Jiskoot, Lize C. (author), Venkatraghavan, Vikram (author), Linders, Jara (author), Aalten, Pauline (author), De Deyn, Peter Paul (author), Niessen, W.J. (author)
This work validates the generalizability of MRI-based classification of Alzheimer's disease (AD) patients and controls (CN) to an external data set and to the task of prediction of conversion to AD in individuals with mild cognitive impairment (MCI). We used a conventional support vector machine (SVM) and a deep convolutional neural network ...
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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Meister, S. (author), Wermes, Mahdieu (author), Stueve, J. (author), Groves, R.M. (author)
In the aerospace industry, automated fibre laying processes are often applied for economical composite part fabrication. Unfortunately, the current mandatory visual quality assurance process takes up to 50% of the entire manufacturing time. An automised classification of manufacturing deviations using Neural Networks potentially improves the...
journal article 2021
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Pastor Serrano, O. (author), Lathouwers, D. (author), Perko, Z. (author)
Background and objective: One of the main problems with biomedical signals is the limited amount of patient-specific data and the significant amount of time needed to record the sufficient number of samples needed for diagnostic and treatment purposes. In this study, we present a framework to simultaneously generate and classify biomedical...
journal article 2021
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Adrianus Ewald, V. (author), Sridaran Venkat, Ramanan (author), Asokkumar, Aadhik (author), Benedictus, R. (author), Boller, Christian (author), Groves, R.M. (author)
Predictive maintenance, as one of the core components of Industry 4.0, takes a proactive approach to maintain machines and systems in good order to keep downtime to a minimum and the airline maintenance industry is not an exception to this. To achieve this goal, practices in Structural Health Monitoring (SHM) complement the existing Non...
journal article 2021
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Doğru, Anil (author), Bouarfa, Soufiane (author), Arizar, Ridwan (author), Aydogan, R. (author)
Convolutional Neural Networks combined with autonomous drones are increasingly seen as enablers of partially automating the aircraft maintenance visual inspection process. Such an innovative concept can have a significant impact on aircraft operations. Though supporting aircraft maintenance engineers detect and classify a wide range of...
journal article 2020
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Liu, Wenqiang (author), Liu, Zhigang (author), Li, Qiao (author), Han, Zhiwei (author), Nunez, Alfredo (author)
This article proposes an automatic high-precision detection method for structure parameters of catenary cantilever devices (SPCCDs) using 3-D point cloud data. The steps of the proposed detection method are: 1) segmenting and recognizing the components of the catenary cantilever devices, 2) extracting the detection plane and backbone...
journal article 2020
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Li, Yong (author), van Oosterom, P.J.M. (author), Ge, Ying (author), Zhang, Xiaoxiang (author), Baart, F. (author)
Sand nourishment is widely adopted as an effective soft approach to provide long-term coastal safety, protect the ecology environment, and promote tourism and recreation. With the increase in frequency and expenses in beach nourishment worldwide, an adequate prediction of morphology evolution is greatly desired for coastline management. Based on...
journal article 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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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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Zhao, Wenzhao (author), Wang, Hongjian (author), Gemmeke, Hartmut (author), van Dongen, K.W.A. (author), Hopp, Torsten (author), Hesser, Jürgen (author)
Image reconstruction of ultrasound computed tomography based on the wave equation is able to show much more structural details than simpler ray-based image reconstruction methods. However, to invert the wave-based forward model is computationally demanding. To address this problem, we develop an efficient fully learned image reconstruction...
journal article 2020
Searched for: subject%3A%22convolutional%255C%2Bneural%255C%2Bnetwork%22
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