How to improve data accessibility for efficient autonomous vehicle development
Mark Pfeiffer, CTO / Co-Founder, SiaSearch | LinkedIn
The meticulous data selection for data-driven technologies generates significant engineering inefficiencies. Sensor data lacks meta-information about content and context and is therefore hard to search.
In this free webinar, Mark Pfeiffer, CTO and Co-Founder of SiaSearch, discusses how data recordings can be made easily accessible through content-based search, and how this helps engineers to accelerate development and improve underlying datasets.
Key topics and takeaways:
- Providing fast and scalable data access is crucial for efficient ADAS and autonomous vehicle development
- For data-driven technologies, smart data can make the difference
- Identifying data which contributes the most to model performance and data which creates biases in the models is crucial for improving performance
- Manual work can deal with research settings but does not scale to the ever-increasing amount of data
- SiaSearch helps you to make the most out of your data and improves the quality of your datasets