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An Adaptive Ensemble Classifier for Steganalysis Based on Dynamic Weighted Fusion
Xikai Xu; Jing Dong; Wei Wang; Tieniu Tan
2015
会议名称International Conference on Communications, Signal Processing, and Systems
会议录名称Proceedings of the 2015 International Conference on Communications, Signal Processing, and Systems
会议日期October 23–24, 2015
会议地点Chengdu, China
摘要Recently, ensemble classifier is predominantly used for steganalysis of digital media, due to its efficiency when working with high-dimensional feature sets and large databases. While fusing the decisions of many weak base classifiers, the majority voting rule is often used, which has the disadvantage that all the classifiers have the same authority regardless of their individual classification abilities. In this paper, we propose a new dynamic weighted fusion method for steganalysis which can be adaptive to input testing samples. For each testing sample, the weight of each base classifier is dynamically assigned according to the distance between the testing sample and the classifier. Experimental results show that the proposed method is able to increase steganalysis performance.
关键词Steganalysis
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/12567
专题智能感知与计算研究中心
通讯作者Jing Dong
推荐引用方式
GB/T 7714
Xikai Xu,Jing Dong,Wei Wang,et al. An Adaptive Ensemble Classifier for Steganalysis Based on Dynamic Weighted Fusion[C],2015.
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