关键词: 数据标注, 标注系统, 深度学习, 智能化

Abstract: The current data labeling platforms and open-source data labeling tools generally have the problem of unreasonable labeling process with multi-people cooperation, which cannot guarantee the efficiency and quality of labeling. To address this problem, this paper proposes a pair annotation method, which uses a way of pair groups, simultaneous annotation and review of each other to annotate. The experiments prove that the pair annotation method can significantly improve the annotation efficiency by 63%. In addition, this paper proposes a speculative annotation method, which reduces the annotation workload to half of the unprojected annotation based on the connection between the data when the input data is video. It is demonstrated that the speculative annotation method can significantly improve the annotation efficiency by 25%.

Key words: data annotation, annotation system, deep learning, intelligence