Released
- Tire wear a tire wear
- Tire size OCR
- Instrument cluster warning lamp recognition
Automate vehicle inspection with Autopedia's precise
artificial
intelligence technology.
Autopedia AI automatically recognizes the tire wear progress, tire size, and warning light status of the vehicle obtained by the existing user as a record once, and delays it to convert the customer's business rate.
Tire size recognition API without problems even if the letters are reversed
A questionable tire size can only be determined by license plate number and vehicle model. Are you worried? Even tire photos that are difficult for humans to identify Identifies the actual vehicle tire size with great accuracy.
Identification of domestic and foreign vehicles and 50 types of warning lights Instrument panel recognition API
"It's a kettle-shaped yellow warning light." 20 warning lights are now over. Regardless of the vehicle type, 50 types of warning lights are automatically identified with a picture of the vehicle's instrument panel and guidance is given on how to take action.
With artificial intelligence learned from photos recorded with various vehicle types, regions, recent, illumination, and angles, it accurately recognizes even low-light environments and objects that were born.
Are you considering launching a global service? Designed to meet international standards, it recognizes all warning lights and tires of vehicles around the world. Leverage AI technology without border restrictions.
All of Autopedia's APIs automatically identify photos that our artificial intelligence model can't analyze, prompting users to retake them. Aim for clear recognition in advance, reflected by photography.
Starting with tire wear, tire size and warning light recognition
technology,
We are creating an AI platform that solves
vehicle problems and concerns of drivers and mobility companies.
Autopedia Revealed Driver First AI Tech in AI Expo Korea 2023
Global Tire Manufactuer, Hankook Tire Adopted Dr.Tread
Autopedia Raises $10 M in Series A
Autopedia Won 1st Prize in Image Recognition Challenge by Ministry of Science and ICT, South Korea
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