This study on Autonomous Driving Data Annotation/ Labeling includes:

  • An analysis on the AI and Machine learning trend and penetration rate in Automotive application
  • Analysis on the sensor data annotation for ADAS and Autonomous application –Radar, Camera, LiDAR
  • Analysis on the techniques, and tools of Data Annotation in the Deep learning models of AVs
  • Analysis on the partnership ecosystem of OEMs with technology players
  • Analysis on the recent M&As in the annotation ecosystem and its impact on the market share of the leading players across the supply chain
  • Data Annotation types and trends –Manual Ground Truth and software automation
  • Data Annotation classification- Semantic annotation, 2D/3D cuboid bounding boxes, polyline and polygons, text and linguistic.
  • Market share analysis, market size in terms of revenue for a period of 2020 to 2026, pricing analysis of annotation/ labeling data along with the varying cost structure with respect to companies
  • Competition assessment of major players- year of experience in the industry, products/techniques, solutions offered, pricing model, funding/investment, major customers, partners, suppliers, industry ranking