Automated vehicles generate up to 10 TB of data per hour and robust autonomous driving starts with understanding this data in depth. In order to leverage the sensor data, engineers spent up to 75% of their time manually exploring, curating and selecting this data. Today, they cannot rely on common tools, because the raw data is unstructured, which prohibits the use of status quo databases. As a result productivity and progress are much lower than would be necessary.
In this free webinar, Clemens Viernickel and Mark Pfeiffer, the Co-Founders of SiaSearch, will discuss how raw data masses can be made easily accessible through automatic indexing and content-based search.
We will explore in depth the use of advanced tooling for understanding, visualizing, curating, and collaborating on your data — allowing teams to work twice as fast to build better software via a powerful interface and API.
Register for the webinar today to learn more about the idea, technology and vision behind SiaSearch, which could help you build better models and data sets, with less effort.
Key Learning Objectives
- Understand how for data-driven technologies, intelligent data handling makes all the difference
- How to use metadata and advanced tooling to explore, understand and curate data for efficient ADAS and autonomous vehicle development
- Improve model performance by identifying biases in your data and discovering rare sequences
- Building a data architecture and database that can scale linearly as data continues to grow
- How use APIs to transform tedious trial and error data review into a magical data playground
Audience
- Automated Driving
- Head of R&D
- VP R&D
- Director of R&D
- R&D lead
- R&D Engineer
- Senior R&D Engineer
- Validation Engineer
- Verification Engineer
- Validation Specialist
- Director of Data Annotation and Labeling Department
- Head of Data Annotation and Labeling
- Manager ADAS
- Perception Engineer
