What is Data Annotation and Why is it Needed?
- 先進運転支援システム (ADAS)
How well are your AI algorithms performing? Data annotation plays a key role in training algorithms, as well as determining how well they perform. AI algorithms have to be taught how to detect other vehicles, pedestrians, road signs, objects, lanes, etc., and they have to be validated through benchmarking of a data subset.
In this podcast, Philip Kessler, Managing Director of understand.ai (a dSPACE company), will provide an overview on what data annotation is, why it is needed, how to get the right data for your algorithms, and how to automate the process.
Co-Founder and CTO understand.ai