文件名称:04
- 所属分类：
- 图形图像处理(光照,映射..)
- 资源属性：
- [PDF]
- 上传时间：
- 2012-11-26
- 文件大小：
- 5.67mb
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- 0次
- 提 供 者：
- 刘*
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如何面对人们日常生活中接触到的，尤其是互联网上数量激增的图像进行有
效的分类，已经成为研究的新热点。虽然现有的图像分类技术已经取得不错的性
能，但是它们还存在着一些问题。一是大部分现有的图像分类算法都是基于图像
的底层特征，’无法解决图像分类中的“语义鸿沟”问题；二是，大多数图像分类算
法总是忽视图像中部分与部分之间的空间关系。-How to face contact with people' s daily lives, especially surge in the number of images on the Internet for effective classification, has become the new hot spot. Although the existing image classification techniques have made a good performance, but they still exist some problems. First, most of the existing image classification algorithms are based on the underlying characteristics of the image, ' can not solve image classification in the " semantic gap" problem Second, most of the image classification algorithm is always ignored and some parts of the image between spatial relationships.
效的分类，已经成为研究的新热点。虽然现有的图像分类技术已经取得不错的性
能，但是它们还存在着一些问题。一是大部分现有的图像分类算法都是基于图像
的底层特征，’无法解决图像分类中的“语义鸿沟”问题；二是，大多数图像分类算
法总是忽视图像中部分与部分之间的空间关系。-How to face contact with people' s daily lives, especially surge in the number of images on the Internet for effective classification, has become the new hot spot. Although the existing image classification techniques have made a good performance, but they still exist some problems. First, most of the existing image classification algorithms are based on the underlying characteristics of the image, ' can not solve image classification in the " semantic gap" problem Second, most of the image classification algorithm is always ignored and some parts of the image between spatial relationships.
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基于词袋模型的图像分类方法研究.pdf