一种基于ResNet网络模型的探地雷达地下空洞目标自动识别方法
The automatic identification method for underground cavity targets using ground penetrating radar based on the ResNet network model solves the problems of missed detection and false detection in existing technologies, and achieves efficient identification of underground cavity targets with an identification rate of over 90%.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- HARBIN INST OF TECH
- Filing Date
- 2022-07-26
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies are insufficient for efficiently identifying underground cavities in ground-penetrating radar images, resulting in missed detections and false detections, and obtaining underground cavity samples is also difficult.
An automatic identification method for underground cavities in ground-penetrating radar based on the ResNet network model is proposed, which includes background removal, gain processing, noise reduction, pre-screening and image augmentation. ResNet18, ResNet34 and ResNet50 are used for training and identification.
It has improved the identification probability of underground cavity targets to over 90%, solved the problems of missed detection and false detection, and realized automated identification of underground cavity targets.
Smart Images
Figure CN115311532B_ABST