山西大学学报（自然科学版）2020，Vol.43Issue(4)：914-926,13.DOI:10.13451/j.sxu.ns.2020081
基于多粒度序贯三支决策的代价敏感目标检测方法
Cost-Sensitive Multi-Granularity Sequential Three-Way Decision for Object Detection
摘要
Abstract
Many studies on object detection attempt to achieve a low misclassification error and they assume the misclassification costs are the same.Such assumption is unreasonable in many real-world applications due to the different costs and insufficient object information.Imbalanced misclassification costs and insuffi-cient information may lead to higher cost.To solve the issue,we propose a cost-sensitive multi-granularity sequential three-way decision method for Object Detection.The proposed method is based on sequential three-way decision(3WD)considering multi-granularity features.It develops a decision strategy which can minimize the total cost in the detection process.In each step,it optimizes the misclassification cost and makes delayed decision if the object information is insufficient.In the method,the object information con-verts from rough granularity to precise granularity in object detection and it may reach more reasonable de-cision.The experiments on several object detection databases are conducted to validate the effectiveness of the proposed method.关键词
序贯三支决策/粒计算/代价敏感学习/目标检测Key words
sequential three-way decision/granular computing/cost-sensitive learning/object detection分类
信息技术与安全科学引用本文复制引用
孙勇,李华雄..基于多粒度序贯三支决策的代价敏感目标检测方法[J].山西大学学报（自然科学版）,2020,43(4):914-926,13.基金项目
国家自然科学基金(71671086 （）
71732003) （）
国家重点研发计划(2016YFD0702100) （2016YFD0702100）
