Searched for: subject%3A%22convolution%22
(101 - 120 of 229)

Pages

document
Yousefi, Sahar (author), Sokooti, Hessam (author), Elmahdy, Mohamed S. (author), Lips, Irene M. (author), Shalmani, Mohammad T.Manzuri (author), Zinkstok, Roel T. (author), Dankers, Frank J.W.M. (author), Staring, M. (author)
Manual or automatic delineation of the esophageal tumor in CT images is known to be very challenging. This is due to the low contrast between the tumor and adjacent tissues, the anatomical variation of the esophagus, as well as the occasional presence of foreign bodies (e.g. feeding tubes). Physicians therefore usually exploit additional...
journal article 2021
document
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
document
Qu, Dingran (author), Qiao, Tiezhu (author), Pang, Y. (author), Yang, Yi (author), Zhang, Haitao (author)
Belt conveyor is considered as a momentous component of modern coal mining transportation system, and thus it is an essential task to diagnose and monitor the damage of belt in real time and accurately. Based on the deep learning algorithm, this present study proposes a method of conveyor belt damage detection based on ADCN (Adaptive Deep...
journal article 2021
document
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
document
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
document
Li, G. (author), Knoop, V.L. (author), van Lint, J.W.C. (author)
Accurate and explainable short-term traffic forecasting is pivotal for making trustworthy decisions in advanced traffic control and guidance systems. Recently, deep learning approach, as a data-driven alternative to traffic flow model-based data assimilation and prediction methods, has become popular in this domain. Many of these deep learning...
journal article 2021
document
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
document
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
document
van Neerven, J.M.A.M. (author), Veraar, M.C. (author)
We prove a new Burkholder–Rosenthal type inequality for discrete-time processes taking values in a 2-smooth Banach space. As a first application we prove that if (S(t, s)) <sub>⩽</sub><sub>s</sub><sub>≤</sub><sub>t</sub><sub>⩽</sub><sub>T</sub> is a C-evolution family of contractions on a 2-smooth Banach space X and (Wt)t∈[0,T] is a...
journal article 2021
document
Wu, L. (author), Perin, G. (author)
In recent years, the advent of deep neural networks opened new perspectives for security evaluations with side-channel analysis. Profiling attacks now benefit from capabilities offered by convolutional neural networks, such as dimensionality reduction and the inherent ability to reduce the trace desynchronization effects. These neural...
conference paper 2021
document
Zhu, B. (author), Hofstee, H.P. (author), Lee, Jinho (author), Al-Ars, Z. (author)
Attention mechanism has been regarded as an advanced technique to capture long-range feature interactions and to boost the representation capability for convolutional neural networks. However, we found two ignored problems in current attentional activations-based models: the approximation problem and the insufficient capacity problem of the...
conference paper 2021
document
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
document
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
document
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
document
van Leeuwen, Bodine (author)
When building a convolutional neural network, many design choices have to be made. In the case of Deepfake detection, there is no readily implementable recipe that guides these choices. This research aims to work towards understanding the effects of design choices in the case of Deepfake detection, using the Python library Keras and publicly...
master thesis 2020
document
Rijsdijk, Jorai (author)
Side-channel attacks (SCA), which use unintended leakage to retrieve a secret cryptographic key, have become more sophisticated over time. With the recent successes of machine learning (ML) and especially deep learning (DL) techniques against cryptographic implementations even in the presence of dedicated countermeasures, various methods have...
master thesis 2020
document
den Ottelander, Tom (author)
Computer vision tasks, like supervised image classification, are effectively tackled by convolutional neural networks, provided that the architecture, which defines the structure of the network, is set correctly. Neural Architecture Search (NAS) is a relatively young and increasingly popular field that is concerned with automatically optimizing...
master thesis 2020
document
Lacoa Arends, Eric (author)
The increasing penetration of weather-dependent energy sources brings additional challenges to the operation of the power system. Wind power forecasting is a valuable resource for these power operators: a tool that aids the decision-making process and facilitates risk management. On the other hand, the progress of machine learning and their...
master thesis 2020
document
Barad, Kuldeep (author)
Autonomous vision-based navigation is a crucial element for space applications involving a potentially uncooperative target, such as proximity operations for on-orbit servicing or active debris removal. Due to low mass and power characteristics, monocular vision sensors are an attractive choice for onboard vision-based navigation systems. This...
master thesis 2020
document
Snel, Koen (author)
The ongoing demand for bigger and more efficient ships pushes their designs towards the strength limits. Sometimes, ship structures are pushed beyond their limits with the possibility of significant negative economic and environmental impact or, in the worst case, impact on human life. This makes it explicitly clear why the development of...
master thesis 2020
Searched for: subject%3A%22convolution%22
(101 - 120 of 229)

Pages