What question did this study set out to answer?

The aim is to highlight AI methods for big data processing in validating Advanced Driver-Assistance Systems (ADAS).

March 12, 2026Open Access

Use of AI for Big Data Processing and Understanding for Validation of ADAS - EXAKI training

TCThe EXA4MIND Consortium DHDavid HurychInstitute of Informatics of the Slovak Academy of Sciences

Key Points

The aim is to highlight AI methods for big data processing in validating Advanced Driver-Assistance Systems (ADAS).
Presentation on methods for processing image, LiDAR, and text data
Description of unsupervised machine learning models
Discussion of the EXA4MIND project's data management strategies using supercomputers and cloud technologies
Insights into the effectiveness of AI models for data validation in ADAS
Demonstrated capacity for handling extremely large datasets
Enhanced understanding of unsupervised learning's role in data analysis

Abstract

In this EXA4MIND training, David Hurych (Valeo) presents the latest methods and AI models for processing image, LiDAR, and text data used in the validation of ADAS before they are deployed on the road in real traffic. The presentation also describes unsupervised machine learning methods developed within the platform for extreme data EXA4MIND project for the transfer, storage, and analysis of extremely large-scale data using supercomputers and cloud technologies.

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