An improved cluster labeling method for support vector clustering 论文
2005IEEE Transactions on Pattern Analysis and Machine Intelligence引用 269
Face and Expression RecognitionRemote Sensing and Land UseImage Retrieval and Classification Techniques
详细信息
- 发表期刊/会议
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- 发表日期
- 2005-01-31
- 发表年份
- 2005
关键词
Face and Expression RecognitionRemote Sensing and Land UseImage Retrieval and Classification Techniques
摘要
The support vector clustering (SVC) algorithm is a recently emerged unsupervised learning method inspired by support vector machines. One key step involved in the SVC algorithm is the cluster assignment of each data point. A new cluster labeling method for SVC is developed based on some invariant topological properties of a trained kernel radius function. Benchmark results show that the proposed method outperforms previously reported labeling techniques.