通信学报Issue(1)：107-114,8.DOI:10.3969/j.issn.1000-436x.2014.01.013
最小差异采样的主动学习图像分类方法
Minimal difference sampling for active learning image classification
摘要
Abstract
Aiming at the problem of measuring the voting disagreement of committee, a minimal difference sampling method for image classification was proposed. It selects the sample with the minimal difference of two highest class probabilities voted by committee. The experimental results show that this method effectively enhances the classification accuracy compared with EQB and nEQB. Furthermore, the influence of the number of models in the decision-making committee was analyzed and discussed. The experimental results show that the proposed method always outperforms nEQB with the same number of models.关键词
图像分类/主动学习/采样策略/委员会投票/最小差异Key words
image classification/active learning/sampling strategy/committee voting/minimal difference分类
信息技术与安全科学引用本文复制引用
吴健,盛胜利,赵朋朋,崔志明..最小差异采样的主动学习图像分类方法[J].通信学报,2014,(1):107-114,8.基金项目
国家自然科学基金资助项目（61003054，61170020）；江苏省科技支撑计划基金资助项目（BE2012075）；江苏省高校自然科学研究基金资助项目（13KJB520021）@@@@The National Natural Science Foundation of China (61003054，61170020) （61003054，61170020）
Jiangsu Province Science and Tech-nology Support Program (BE2012075) （BE2012075）
Jiangsu Province Colleges and Universities Natural Science Research Project (13KJB520021) （13KJB520021）
