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Image Annotation Image recognition Automotive

Advancing Accurate Traffic Sign Classification and Damage Detection for Safer Road Traveling

 

The Challenge

Our client, a long-standing partner and leader in the automotive industry, sought to enhance their models’ ability to detect and segment US traffic signs. Across 50,000 images, each sign had to be annotated for:

  • Sign class – one of 120+ categories, including “other” and “multiple.”
  • Damage class – condition labels such as “faded,” “broken,” or “vandalized.”

• • • •The Solution• • • •

DataForce leveraged our proprietary platform, an experienced project management team, and several innovative approaches to ensure efficient and accurate annotations while enabling scalability:

  1. Close Client Collaboration to Define Data Goals
    • Engaged early with the customer to identify ambiguous cases, set rules for complex scenarios, and refine sign classification rules and damage definitions.
    • Built comprehensive guidelines, including decision trees, a class register, and a dynamic visual reference folder.
  2. Active Engagement with the Annotation Team 
    • Regularly updated edge cases, guidelines, and core project documentation to ensure annotators had clear, consistent direction.
    • Flagged difficult images for expert review and applied targeted QA for annotators with lower accuracy, providing additional oversight and coaching.
  3. Tech-Enabled Workflow Optimization
    • Image Pre-Processing: Used dual cropping (tight/loose) for speed and accuracy.
    • Automated Pre-Classification: Leveraged a fine-tuned ResNet-101 model and an AI-powered sign detection tool to generate initial classifications before human validation. The model, trained using labeled sign crops and capable of recognizing over 120 traffic sign types, correctly matched the final human-reviewed annotations on its first prediction 40% of the time.
  4. Quality Assurance & Performance Monitoring
    • Implemented multi-level reviews supported by automated performance tracking to analyze pre- vs post-review accuracy trends.
  5. Automated Final Processing & Visual Validation
    • Processed final annotations into structured JSON format with bulk visual validation.

Results

DataForce met and exceeded the client’s stringent requirements:

  • 100% acceptance rate: no negative feedback.
  • 54,000 additional images: requested post-delivery, increasing total delivered scope to 104,000.

Thanks to DataForce’s advanced annotation process and efficient workflows, the client enhanced their algorithms, accelerated development timelines, and frequently praised our team’s problem-solving and results-driven approach—ultimately advancing their ability to navigate complex traffic scenarios.

DataForce has a global community of over 1,000,000 members from around the globe and linguistic experts in over 250 languages. DataForce is its own platform but can also use client or third-party tools. This way, your data is always under control.

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