Searched for: contributor:"Kooij, Julian (mentor)"
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Ammerlaan, Jelle (author)
Self-driving vehicles have shown rapid development in recent years and continue to move towards full autonomy. For high or full automation, self-driving vehicles will have to be able to address and solve a broad range of situations, one of which is interaction with traffic agents. For correct and save maneuvering through these situations,...
master thesis 2020
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Glastra, Thom (author)
The bottleneck of the maximum road volume in urban areas is the maximum capacity of the traffic flow on the intersection, which is coordinated with Traffic Light Controllers (TLCs). A promising method to decrease the number of stops are Green Light Optimal Speed Advice (GLOSA) systems. These systems will give a speed advice to arriving vehicles...
master thesis 2020
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van Schouwenburg, Sietse (author)
Simultaneous Localization And Mapping (SLAM) algorithms provide accurate localization for autonomous vehicles and provide essential information for the path planning module. However, SLAM algorithms as- sume a static environment in order to estimate a location. This assumption influences the pose estimation in dynamic urban environments. The...
master thesis 2019
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Bos, Evert (author)
With an in vehicle camera many different things can be done that are essential for ADAS or autonomous driving mode in a vehicle. First, it can be used for detection of general objects, for example cars, cyclists or pedestrians. Secondly, the camera can be used for traffic light recognition, which is localization of traffic light position and...
master thesis 2019
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van Laar, Patrick (author)
New measures have to be taken to combat fatalities caused by traffic accidents. Intelligent vehicles have the potential to increase safety, but depend heavily on their automated perception ability.<br/>Acoustic perception, an unused sensing modality in this field, has potential for the detection of nearby vehicles, an ability both human drivers...
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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Hafner, Frank (author)
Cross-modal person re-identification is the task to re-identify a person which was sensedin a first modality, like in visible light (RGB), in a second modality, like depth. Therefore, the challenge is to sense between inputs from separate modalities, without information from both modalities at the same time step. Lately, the scientific challenge...
master thesis 2018
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Wang, Ziqi (author)
This work explores the possibility of incorporating depth information into a deep neural network to improve accuracy of RGB instance segmentation. The baseline of this work is semantic instance segmentation with discriminative loss function.The baseline work proposes a novel discriminative loss function with which the semantic net-work can learn...
master thesis 2018
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Zijlmans, Jeroen (author)
To bring down the number of traffic accidents and increase people’s mobility companies, such as Robot Engineering Systems (RES) try to put automated vehicles on the road. RES is developing the WEpod, a shuttle capable of autonomously navigating through mixed traffic. This research has been done in cooperation with RES to improve the localization...
master thesis 2018
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van Dorth, Matthijs (author)
master thesis 2017
Searched for: contributor:"Kooij, Julian (mentor)"
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