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Study of semantic segmentation applications for autonomous vehicles

Sanchez Escalonilla Plaza, S. (2019) Study of semantic segmentation applications for autonomous vehicles.

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Abstract:Autonomous Vehicles are machines capable of navigating the environment without human intervention. Such an interaction with the environment requires of a system that provides the vehicle with accurate information about the surroundings, this is called scene understanding. Scene understanding includes obtention, processing and analysis of data. There are different ways of obtaining information from the environment although the most common one is through the use of cameras. Cameras can obtain visual information of the surroundings in the same way humans do. There are different techniques that allow the user to learn from its composition depending on the final goal and the required level of accuracy. Some of the applications of these techniques are: image classification, object detection, object tracking or semantic image segmentation. Semantic image segmentation provides insight about the composition of the image in the highest possible detail. It consists on the pixel-label classification of the image. Semantic image segmentation can be very useful for navigation scenarios, allowing to create an accurate representation of the environment.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Programme:Electrical Engineering MSc (60353)
Link to this item:http://purl.utwente.nl/essays/80962
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