Use Cases

Enhancing AI with High-Quality Image Annotation

Industry: Autonomous Vehicles

Client Goal:

A US-based autonomous vehicle startup needed annotated visual data to train its object detection and path planning algorithms for real-time navigation and obstacle avoidance.

Solution by Shighi Technologies:
Shighi Technologies provided detailed bounding box, polyline, and semantic segmentation annotation for over 250,000 images captured by the vehicle’s onboard cameras. Our annotation team ensured high consistency and class accuracy across categories like pedestrians, traffic signs, lane markings, and vehicles.

Outcome:

• Reduced model error rate by 32% after incorporating annotated data
• Accelerated model training and deployment time by 40%
• Achieved 98%+ annotation accuracy under strict QA review