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The License Plate Anonymizer is a localization and blurring algorithm designed to consistently anonymize vehicle license plates. This algorithm can be used in real-time, ensuring absolute compliance with GDPR regulation, or on video footage before public release. The License Plate Anonymizer parameters are easily customizable according to project needs and local legislation.
PERFORMANCE
Optimized for edge performance with a low power profile.
PERSPECTIVE
Ground-to-ground.
CONDITIONS
Dawn to dusk and artificial lightning.
ENVIRONMENT
Environmentally agnostic performance.
ARCHITECTURE
Backbone: Resnet-101; Detector: RefineDet.
FUNCTIONALITY
Detection.
INPUT SIZE
512x512.
SENSOR MODALITY
Visible light.
Our services
MAINTENANCE
Each CVEDIA model comes backed with an ongoing maintenance agreement. Our team is available for continuous improvements and to ensure upkeep.
FINE GRAIN CLASSIFICATION
Speak to our team to discuss model classification as a service add on or as a separate model. CVEDIA’s in-house team will work with you to define your requirements, and build a synthetic-based model incorporating your classification specifications.
ADDITIONAL CLASSES
CVEDIA models are built using proprietary synthetic data technology, meaning adding additional classes to your model is possible in a matter of weeks.
Use cases
GDPR COMPLIANCE
Ensure your machine learning application complies with GDPR legislation in real-time. The License Plate Anonymizer has a low power profile, making it simple to add to existing computing resources on intersection cameras, security systems, and vehicles.
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