Thesis supervisor: Levente Hajder
Location of studies (in Hungarian): Eötvös Loránd tudományegyetem Abbreviation of location of studies: ELTE
Description of the research topic:
The field of research in ADAS (Advanced Driver Assistance System) continues to be intriguing as the automotive industry's sensors evolve with each generation. Additionally, new use-cases and challenges arise due to the increasing population in cities and denser traffic in rural areas. One crucial aspect of this field is environmental modeling, particularly with a commercially viable sensor set that meets the market demands of the automotive industry.
In the context of this PhD thesis, the topic focuses on utilizing machine learning techniques to develop an environmental modeling system having the current solutions as benchmark with the aim to enhance the performance of the predictions, enabling the deployment of more advanced ADAS functionalities.
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