What is Where? Visual Understanding for Autonomous Cars

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dc.contributor.authorGrenier, Amélie
dc.date.accessioned2024-05-05T09:52:11Z
dc.date.available2024-05-05T09:52:11Z
dc.date.issued2020-01-09 11:36
dc.description.abstractAutonomous driving has been rapidly evolving for the last few years and there is a lot of fervour in increasing the intelligence of these vehicles. One key aspect of a self-driving car is its ability to sense the environment in order to be aware of its surroundings and consecutively take better decisions.While the right combination of sensors is widely debated, my research interest lies in using computer vision and machine learning techniques to detect, localise and recognise surrounding entities. My talk will describe my research objectives and the expected outcome. It will address some of the encountered challenges, resulting from the urban traffic environment context and my sensor choice. It will include a mention of the algorithms that I have tested so far and those currently in development. You will have a glance at some of the questions that researchers are presently trying to answer in this interdisciplinary field.
dc.identifier.citationGrenier, Amélie (2020). What is Where? Visual Understanding for Autonomous Cars. Cranfield Online Research Data (CORD). Presentation. https://doi.org/10.17862/cranfield.rd.11558580.v1
dc.identifier.doi10.17862/cranfield.rd.11558580.v1
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/21434
dc.publisherCranfield University
dc.rightsCC BY 4.0
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject'Scene understanding'
dc.subject'Machine learning'
dc.subject'Autonomous driving'
dc.subject'DSDS19'
dc.subject'DSDS19 3MT'
dc.subject'Autonomous Vehicles'
dc.subject'Computer Vision'
dc.subject'Knowledge Representation and Machine Learning'
dc.titleWhat is Where? Visual Understanding for Autonomous Cars
dc.typePresentation

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