LEARNING
学习标注延迟和误报AEB事件：应对极端类别不平衡与非对称标签噪声的实用系统
Mengxiang Hao, Xin Jiang, Xinghao Huang, Wenliang Su, Zhiteng Wang, Junjie Rao, Xiaotian Yang, Wei Liao, Chengyu Han, Gen Liang, Yulun Song, Zhitao Xu, Xianpeng Lang
- 发表年份
- 2026
- 访问权限
- 开放获取
摘要
本文提出了首个自动标注AEB事件的框架，解决了延迟/误报触发事件中极端类别不平衡和非对称标签噪声的挑战。通过特定数据增强和噪声抑制技术，该框架能高效识别占比不足5%的关键少数样本。
关键词
AEB annotationclass imbalancelabel noisedata augmentationautonomous driving
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