Data Annotation Quality Problems in AI-Enabled Perception System Development
Abstract
This paper reports a multi-organisation case study on data annotation for AI-enabled perception systems in automated driving, identifying a taxonomy of recurring annotation error types across completeness, accuracy, and consistency dimensions.
Type
Publication
arXiv preprint arXiv:2511.16410
Mazen Mohamad
Researcher at RISE Research Institutes of Sweden
My research interests include Safety & Cybersecurity of Autonomous Systems, AI4Security, and Security4AI.