基于人工智能的倒车镜损伤检测方法及相关设备
By preprocessing historical vehicle damage images and training models, the problem of low accuracy in rearview mirror damage detection was solved, and high-precision rearview mirror damage recognition was achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- PING AN TECH (SHENZHEN) CO LTD
- Filing Date
- 2022-07-28
- Publication Date
- 2026-07-17
AI Technical Summary
Existing image processing technologies cannot perform fine-grained segmentation of vehicle components, resulting in low accuracy in detecting damage to rearview mirrors.
By preprocessing historical vehicle damage images, a vehicle component segmentation model and a rearview mirror damage detection model are trained. The vehicle component segmentation model is used to segment the vehicle image to be detected, and the rearview mirror damage detection model is used to detect damage, thus achieving end-to-end rearview mirror damage recognition.
The accuracy of rearview mirror damage detection has been improved. A robust vehicle damage recognition model has been trained using a large amount of historical vehicle data, achieving high-precision rearview mirror damage recognition.
Smart Images
Figure CN115222943B_ABST