Searched for: subject%3A%22Semantic%255C%2BSegmentation%22
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Bai, Qian (author)
Roads in modern cities facilitate different types of users, including car drivers, cyclists, and pedestrians. These different users often have a designated section of the road to operate on. Road management, e.g., by municipalities, needs to take this sectioning into account, preferably in an efficient way. Mobile laser scanning (MLS) point...
master thesis 2021
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Bai, Qian (author)
Semantic segmentation of aerial point clouds with high accuracy is significant for many geographical applications, but is not trivial since the data is massive and unstructured. In the past few years, deep learning approaches designed for 3D point cloud data have made great progress. Pointwise neural networks, such as PointNet and its extensions...
student report 2020
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Mulder, Amber (author)
Semantic segmentation (or pixel-level classification) of remotely sensed imagery has shown to be useful for applications in fields as mapping of land cover, object detection, change detection and land-use analysis. Deep learning algorithms called convolutional neural networks (CNNs) have shown to outperform traditional computer vision and...
master thesis 2020
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Autar, Ravi (author)
Person re-identification (re-ID) is a task that aims to associate the same people across different cameras. One of the many important problems a person re-ID system has to address in order to achieve good performance is the feature misalignment problem. Past research has attempted to address this problem by using attention networks, pose...
master thesis 2019
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Lengyel, Attila (author)
This work investigates how prior knowledge from physics-based reflection models can be used to improve the performance of semantic segmentation models under an illumination-based domain shift. We implement various color invariants as a preprocessing step and find that CNNs trained on these color invariants get stuck in worse local minima...
master thesis 2019
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Zhou, Zequn (author)
Urban areas are rapidly expanding in developing countries. One of goals of the United Nations Human Settlement Programme (UN-Habitat) is to understand and guide urban development for some developing regions.<br/>Currently, the approaches that UN-Habitat is using cost plenty of workforce, material, and time. Therefore, UN-Habitat is interested in...
master thesis 2019
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Ai, Zhiwei (author)
Deep learning methods have been demonstrated to be promising in semantic segmentation of point clouds. Existing works focus on extracting informative local features based on individual points and their local neighborhood. They lack consideration of the general structures and latent contextual relations of underlying shapes among points. To this...
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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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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Steensma, Bart (author)
Fouling (algae, slime, and barnacles) on the hull of large cargo vessels is undesirable because it increases their frictional drag, resulting in an increased fuel consumption. As a solution, Fleet Cleaner introduced a ship hull cleaning robot that maneuvers on the hull, using powered wheels and magnets. The robot is controlled by a human...
master thesis 2018
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Kolenbrander, Thomas (author), van Oort, Bart (author), de Ruiter, Frank (author), Yue, Tim (author)
This report describes the process of the Bachelorproject(TI3806) done for ‘De Energiebespaarders’, a startup in Amsterdam striving to make homes more energy efficient through accessible advice and installation of insulation or solar panels. The goal of the project was to apply machine learning to improve their system for identifying house...
bachelor thesis 2017
Searched for: subject%3A%22Semantic%255C%2BSegmentation%22
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