现代信息科技2024，Vol.8Issue(16)：34-38,5.DOI:10.19850/j.cnki.2096-4706.2024.16.008
多模型融合投票预标注算法研究
Research on Pre-labelling Algorithm for Multi-model Fusion Voting
吉星 1陈喆 1陈飞扬 1杨文听 1樊桢珍 1许丹1
作者信息
- 1. 陕西重型汽车有限公司,陕西 西安 710000
- 折叠
摘要
Abstract
Aiming at the two problems of cumbersome and time-consuming annotation content,a pre-labelling algorithm for multi-model fusion voting is proposed.In the pre-labelling process,the detection results of the three models of Cascade_RCNN,RetinaNet and CondLaneNet are fused,and then the coordinate results generated by each model are processed by extracting,judging,matching,averaging of parameters,sorting and so on,to obtain the final pre-labelling results.The results of multiple tests on the public datasets and the self-constructed datasets show that the algorithm is able to improve the accuracy of pre-labelling and reduce the manual labelling workload in the process of labelling,which has a better effect and verifies the effectiveness of the method.关键词
深度学习/目标检测/车道线检测/预标注/模型融合Key words
Deep Learning/target detection/laneline detection/pre-labelling/model fusion分类
信息技术与安全科学引用本文复制引用
吉星,陈喆,陈飞扬,杨文听,樊桢珍,许丹..多模型融合投票预标注算法研究[J].现代信息科技,2024,8(16):34-38,5.
