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| 图学习的区域图像标注方法 | |
| 引用本文： | 虎晓红,钱旭,王珂.图学习的区域图像标注方法[J].计算机应用,2009,29(9). |
| 作者姓名： | 虎晓红 钱旭 王珂 |
| 作者单位： | 1. 河南农业大学,信息与管理科学学院,郑州,450002;中国矿业大学,机电与信息工程学院,北京,100083 2. 中国矿业大学,机电与信息工程学院,北京,100083 3. 首都医科大学,生物医学工程学院,北京,100069 |
| 摘 要： | 近年来,图像标注技术得到广泛关注.提出一种图学习的自动图像标注方法,将图像标注作为多示例学习框架下的半监督学习策略,通过给出适合图像在包空间的有效度量方式,充分利用未标注样本挖掘图像特征的内在规律性,将半监督学习的方法和多示例学习有效结合起来,从而获得更准确的标注结果.实验结果表明,提出的标注方法可行,同时标注结果与传统的标注方法相比得到了明显提高. |
| 关 键 词： | 多示例学习 半监督学习 自动图像标注 图学习 区域匹配 |
Region-based image annotation of graph learning approach |
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| HU Xiao-hong,QIAN Xu,WANG Ke.Region-based image annotation of graph learning approach[J].journal of Computer Applications,2009,29(9). | |
| Authors: | HU Xiao-hong QIAN Xu WANG Ke |
| Affiliation: | 1.College of Information and Management Science;Henan Agricultural University;Zhengzhou Henan 450002;China;2.School of Mechanical Electronic and Information Engineering;China University of Mining and Technology;Beijing 100083;3.School of Biomedical Engineering;Capital Medical University;Beijing 100069;China |
| Abstract: | Image annotation has been an active research topic in recent years.The authors formulated image annotation as a semi-supervised learning problem under multi-instance learning framework.A novel graph-based semi-supervised learning approach to image annotation,using multiple instances,was presented,which extended the conventional semi-supervised learning to multi-instance setting by introducing the adaptive geometric relationship between two bags of instances.The experimental results show that this approach o... |
| Keywords: | multi-instance learning semi-supervised learning automatic image annotation graph learning region matching |
| 本文献已被 CNKI 万方数据 等数据库收录！ | |