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Yu, Rui (author)
The development of intelligent vehicle and autonomous driving asked a higher requirement of ADAS on its functionality. Currently, ADAS systems are able to detect and segment urban and highway driving scenes. They cannot, in general, extract ’meaning’ from this segmentation yet. Learning the intention of other road users will help ADAS understand...
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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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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Uittenbogaard, Ries (author)
In this thesis, a pipeline is created consisting of two parts. In the first part, the moving objects (cars, cyclists, pedestrians) are detected in street-view imagery using image segmentation neural networks and a LIDAR-based moving object detection approach. In the second part, those moving objects are deleted from the image data and an image...
master thesis 2018
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