Searched for: subject:"Neural%5C+Networks"
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García Sanz, María (author)
Patients with 1p/19q co-deleted low grade glioma (LGGs) have better prognosis and react better to certain treatments than patients with intact 1p/19q LGG. Currently, information about the 1p/19q co-deletion status is obtained by means of an invasive procedure called biopsy. As an alternative, non-invasive techniques to extract this information...
master thesis 2019
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Gulikers, Tom (author)
Engineering fields such as aerospace rely heavily on the Finite Element Method (FEM) as a modelling tool. In combination with the scale and complexity of the structures typically involved here, computational cost remains a traditional issue. To perform FEM analyses of such structures efficiently nonetheless, engineers rely on techniques such as...
master thesis 2018
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Dürnay, Philipp (author)
Autonomous MAV are an emerging technology that supports a wide range of applications such as medical delivery or finding survivors in disaster scenarios. As flying in such missions is difficult the robust estimation of an MAV's state within its environment is crucial to ensure safe operation. In indoor scenarios, cameras are one of the...
master thesis 2018
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Irawan, Angga (author)
Controller synthesis techniques based on symbolic models or discrete abstractions are becoming increasingly attractive as they allow for synthesizing correct-by-design controllers of general nonlinear systems under complex behavioral requirements. However, its immense size as the consequence of the state-space explosion prohibits the approach to...
master thesis 2018
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Koeten, Vincent (author)
Current hospital protocols dictate patients be turned at least every three hours in the effort of preventing pressure ulcers. To reduce the workload of nurses, Momo Medical has created an embedded sensing device to track the patient's posture and notify nurses when it is time to turn them. The challenge presented and the focus of this thesis is...
master thesis 2018
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Bormans, Robbert (author)
Robot Care Systems (RCS) is involved in the development of the WEpod, an autonomous shuttle which can transfer up to six people. Based on a predefined map of the environment, the shuttle is able to navigate through mixed traffic its perception sensors such as camera, radar and lidar sensors. This study is acquired in collaboration with RCS and...
master thesis 2018
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Tijink, Jan (author)
master thesis 2018
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Dhar, Aniket (author)
Convolutional neural networks are showing incredible performance in image classification, segmentation, object detection and other computer vision applications in recent years. But they lack understanding of affine transformations to input data. In this work, we introduce rotational invariant
convolutional neural networks that learn...
master thesis 2018
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Rao, Shashank (author)
Sleep is a natural state of our mind and body during which our muscles heal and our memories are consolidated. It is such a habitual phenomenon that we have been viewing it as another ordinary task in our day-to-day life. However, owing to the current fast-paced, technology-driven generation, we are letting ourselves be sleep-deprived, giving...
master thesis 2018
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Wijnker, Dirk (author)
We investigate how an Unmanned Air Vehicle (UAV) can detect manned aircraft with a single microphone. In particular, we create an audio data set in which UAV ego-sound and recorded aircraft sound can be mixed together, and apply convolutional neural networks to the task of air traffic detection. Due to restrictions on flying UAVs close to...
master thesis 2018
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Kiefer, Joshua (author)
More than half a century after the first application of composite materials in aircraft, the accurate prediction of their failure remains a pressing and unresolved issue. Another important limitation continues to be the low transverse strength of unidirectional composite plies, which can lead to premature failure in common laminates such as the...
master thesis 2018
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Poort, Jonah (author)
Vapor-liquid phase equilibrium (flash) calculations largely contribute to the total computation time of many process simulation models. As a result, process simulations, especially dynamic cases, are limited in the amount of detail that can be included due to time restrictions. In addition, under certain conditions flash calculations can fail to...
master thesis 2018
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Zhong, Shijian (author)
The Train Maintenance Scheduling Problem (TMSP) is a real-world problem that aims at complete maintenance tasks of trains by scheduling their activities on a service site. Common methods of constructing optimal solutions to this problem are difficult as the problem consists of several highly-related sub-problems. Currently, NS is using a lo- cal...
master thesis 2018
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Chen, Shuang (author)
master thesis 2018
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Zhou, Lizhongyang (author)
It is desirable to predict construction cost with a high level of accuracy in the early phase to compare the budgetary with feasibility determinations. Additionally, it is required to be as quick as possible. However, the accuracy of the cost estimation depends on the design details which are extremely limited in such an early phase, rendering...
master thesis 2018
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Haenen, Anner (author)
Heerema Marine Contractors (HMC) is a contractor in the international offshore oil, gas and renewables industry. It is specialized in transporting, installing and removing large offshore facilities. HMC operates three crane vessels. Two of which are semi-submersibles (Thialf and Balder), the other is the monohull Aegir. A third semi-submersible,...
master thesis 2018
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Suryamurthy, Vivekanandan (author)
Intelligent terrain perception for search-and-rescue robotic applications, requires a high-level understanding of both the terrain type and its chief physical characteristics. Roughness is one such important terrain property, since it could play a key role in robot control/planning strategies, while navigating
in an unknown environment. In...
master thesis 2018
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Shi, Xiangwei (author)
We propose a framework to interpret deep convolutional models for visual place classification. Given a deep place classification model, our proposed method produces visual explanations and saliency maps that reveal the understanding of images by the model. To evaluate the interpretability, t-SNE algorithm is used for mapping and visualization of...
master thesis 2018
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Kolthof, Daan (author)
In several machine learning problems, a relatively small subproblem is present in which combinations of (negating) objects or structures result in a negation or otherwise other classification compared to when these (negating) objects are not present. To be more specific, a variant of the XOR problem is present in a small amount of objects in...
master thesis 2018
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Claus, Michele (author)
We propose a novel Convolutional Neural Network (CNN) for Video Denoising called VidCNN, which is capable to denoise videos without prior knowledge on the noise distribution (Blind). VidCNN is a flexible model, since it tackles multiple noise types, artificial and real. The CNN architecture uses a combination of spatial and temporal filtering,...
master thesis 2018
Searched for: subject:"Neural%5C+Networks"
(1 - 20 of 82)

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