Searched for: subject:"Deep%5C+Learning"
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Boehmer, Daniël (author)
Wind energy plays a major role in the ongoing energy transition. To accelerate the adoption of wind energy and thereby the energy transition, the Levelized Cost of Energy (LCOE) has to be minimized. Apart from increasing turbine performance, reducing turbine down-time can contribute to lowering the LCOE.Down-time is defined as time during which...
master thesis 2019
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Sankararaman, Shyam Prasadh (author)
Hyperspectral imaging (HSI) is a promising imaging modality in medical applications, especially for non-invasive and non-contact disease diagnosis and image-guided surgery. Encoding both spatial and spectral information, it can detect subtle changes in the biochemical and morphological properties of a tissue, revealing the early progression of a...
master thesis 2019
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Resink, Tim (author)
To be able to understand the dynamic driving environment, an autonomous vehicle needs to predict the mo- tion of other traffic participants in the driving scene. Motion prediction can be done based on experience and recently observed series of past events, and entails reasoning about probable outcomes with these past ob- servations. Aspects that...
master thesis 2019
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Jargot, Dominik (author)
Nowadays, autonomous driving is a trending topic in the automotive field. One of the most crucial challenges of autonomous driving research is environment perception. Currently, many techniques achieve satisfactory performance in 2D object detection using camera images. Nevertheless, such 2D object detection might be not sufficient for autonomous...
master thesis 2019
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Brand, Patrick (author)
Recent advances in Artificial Intelligence and Computer Vision have been showed to be promising for automated land use classification of remotely sensed data. However, current state-of-the-art per-pixel segmentation networks fail to accurately capture geometrical and topological properties on land use segmentation, as these methods have...
master thesis 2019
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de Jong, Tobias (author)
Enabling mobile robots to autonomously navigate complex environments is essential for real-world deployment in commercial, industrial, military, health care, and domestic settings. Prior methods approach this problem by having the robot maintain an internal map of the world and then use a localization and planning method to navigate through the...
master thesis 2019
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Dritsas, Athanasios (author)
In the last years, the popularity of video-on-demand services has been constantly increasing, especially for the young audiences who are more adept at using new technologies. Through those platforms, the viewers have access to a huge volume of movies at any moment that makes the viewing decision for most of them a very challenging task....
master thesis 2019
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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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de Jong, Richard (author)
Persistent surveillance is an urgent proficiency. For security, surveillance cameras are a strong asset as they support the automatic tracking of people and are directly interpretable by a human operator. Radar on the other hand can be used under a broad range of circumstances: radar can penetrate mediums such as clouds, fogs, mist and snow, and...
master thesis 2019
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Wang, Johnny (author)
The gap between predicted brain age and chronological age could serve as biomarker for early-stage neurodegeneration and as potentially as a risk indicator for dementia. We assess the utility of this age gap as a risk biomarker for incident dementia in a general elderly population. The brain age is estimated from longitudinal brain magnetic...
master thesis 2019
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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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Duan, Wen Jie (author)
Planning grasp poses for a robot on unknown objects in cluttered environments is still an open problem. Recent research suggests that deep learning technique is a promising approach to plan grasp poses on unknown objects in cluttered environments. In this field, three types of data are used for training: (a) human labeled data; (b) synthetic...
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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van Wijnen, Kimberlin (author)
Perivascular spaces (PVS) visible on MRI are currently emerging as an important potential neuroimaging marker for several pathologies in the brain like Alzheimer’s disease and cerebral small vessel disease. PVS are fluid-filled spaces surrounding vessels as they enter the brain. Although PVS are normally not noticeable on MRI scans acquired at...
master thesis 2018
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Tsutsunava, Nick (author)
Kinodynamic planning is motion planning in state space and aims to satisfy kinematic and dynamic constraints. To reduce its computational cost, a popular approach is to use sampling based methods such as RRT with off-line machine learning for estimating the steering cost and inputs. However, scalability and robustness are still open challenges...
master thesis 2018
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Snaauw, Gerard (author)
Cardiac magnetic resonance (CMR) is used extensively in the diagnosis and management of cardiovascular disease. Deep learning methods have proven to deliver segmentation results comparable to human experts in CMR imaging, however, no successful attempts have been made at fully automated diagnosis. This has been contributed to a lack of...
master thesis 2018
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Yin, Yunchao (author)
Coronary artery disease is the most common type of heart disease, which influences 110 million people's health and causes 8.9 million deaths in 2015. Physicians can visualize the lesion in coronary arteries by cardiac angiography (X-ray image) during diagnosis and treatment of coronary artery disease. The pathological findings in cardiac...
master thesis 2018
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van Ramshorst, Arjan (author)
Knowledge on adversaries during military missions at sea heavily influences decision making, making identification of unknown vessels an important task. Identification of surrounding vessels based on visual data offers an alternative to AIS information (Automatic Identification System), the current standard in vessel identification, which can be...
master thesis 2018
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Dijkstra, Timo Johannes (author)
The versatility of the hands is revealed in its movements, but often not noticed before trauma occurs. Joint range of motion is used as a measure to follow the progress of diseases. A digital workflow for 3D data in medical appliances is envisioned for years.
The aim of this research is to develop a method that reliably and reproducability...
master thesis 2018
Searched for: subject:"Deep%5C+Learning"
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