作　　者： ; ; ;

机构地区： 通信与信息工程学院

出　　处： 《控制与决策》 2013年第4期481-488,共8页

摘　　要： 多示例学习(MIL)作为第4种机器学习框架,已在图像语义分析中得到了广泛应用.首先介绍MIL的起源、特点、相关概念和数据集;然后以图像语义分析为应用背景,对相关MIL算法进行详细综述,按照算法采用的学习机制对其进行分类,并重点分析了各类算法提出的思路和主要特点;最后,对MIL未来的研究方向作了探讨. Multi-instance learning（MIL） has been recognized as the fourth machine learning framework, and has been widely used in the image semantic analysis. Firstly, the concepts such as development history, characteristics and many useful testing datasets of MIL techniques are reviewed. Then, many popular MIL algorithms are also introduced in detail by using real- world applications based on image semantic analysis. Meanwhile, based on their machine learning mechanisms, related MIL algorithms are divided into a variety of categories, which highlights the processes and dominant features of different MIL algorithms. Finally, the trends and possible outputs for further researches are discussed in details.

关 键 词： 多示例学习 图像分类 图像检索 图像语义分析

领　　域： [自动化与计算机技术] [自动化与计算机技术]