基于帧间差分优化算法的雾天轨道异物检测方法
王林峰1万衡1刘子仪2秦娜2黄德青2张一鸣2
Method for Detecting Track Abnormal Objects in Foggy Weather Based on Inter-frame Differential Optimization Algorithm
WANG LinfengWAN HengLIU ZiyiQIN NaHUANG DeqingZHANG Yiming
-
作者信息:1.1.上海应用技术大学轨道交通学院， 201400， 上海；
2.2.西南交通大学电气工程学院， 611756， 成都
-
Affiliation:School of Railway Transportation, Shanghai Institute of Technology, 201400, Shanghai, China
-
关键词:
-
Key words:
-
DOI:10.16037/j.1007-869x.2022.10.036
-
中图分类号/CLCN:U216.3
-
栏目/Col:施工技术
摘要:
针对复杂环境和恶劣天气对轨道异物识别造成的干扰，提出帧间差分优化的雾天轨道异物检测方法。引入分权评价实现多帧连续识别的帧间差分优化算法。将该算法与其他检测算法进行消融试验，验证了优化算法的可行性。
Abstracts:
Aiming at the interference on abnormal objects recognition caused by complex environment and bad weather, a track abnormal objects detection method in foggy weather based on inter-frame differential optimization is proposed. Decentralized evaluation is introduced to realize the inter-frame differential optimization algorithm of multi-frame continuous recognition. Ablation experiments are performed with this algorithm and other detection algorithms to verify the feasibility of the optimized algorithm.
- 上一篇: 高铁物流运输模式及其可行性
- 下一篇: 深圳都市圈城际铁路CBTC系统功能需求研究
过刊浏览
资料下载
友情链接