一种道路病害识别方法、装置、电子设备及存储介质
By identifying road defects layer by layer in a deep convolutional neural network model and utilizing defect identification processing at different depth levels, the problem of low identification efficiency in existing technologies is solved, and more efficient defect identification is achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SHENZHEN INTELLIFUSION TECHNOLOGIES CO LTD
- Filing Date
- 2023-04-28
- Publication Date
- 2026-07-17
AI Technical Summary
In current road inspections, the comprehensive identification of road defects suffers from low efficiency, especially when using deep convolutional neural network models, which require high computational resources and have slow identification speed.
By performing disease identification processing on the image to be identified at different depth levels, and using a deep convolutional neural network model, the disease identification results with high confidence are identified layer by layer, avoiding the extraction of unnecessary feature information at deeper levels and reducing the amount of computation.
It improves the efficiency of road defect identification by reducing the consumption of computing resources and increasing the identification speed through layer-by-layer identification and output of high-confidence results.
Smart Images
Figure CN116563809B_ABST