| 支持向量机增量学习的算法与应用 |
| |
| 引用本文： | 曾文华,马健. 支持向量机增量学习的算法与应用[J]. 计算机集成制造系统, 2003, 9(Z1): 144-148 |
| |
| 作者姓名： | 曾文华 马健 |
| |
| 作者单位： | 1. 厦门大学计算机科学系,福建,厦门,361005
2. 杭州电子工业学院计算机分院,浙江,杭州,310037 |
| |
| 基金项目： | 工业控制技术国家重点实验室开放实验室研究课题资助项目(K01001). |
| |
| 摘 要： | 提出一种新的支持向量机的增量学习算法,分析了新样本加入训练集后支持向量集的变化情况.基于分析结论提出一种新的学习算法.研究了基于支持向量机的山羊绒和细支绵羊毛动物纤维图像识别问题,根据山羊绒和细支绵羊毛动物纤维图像的特点,分别采用自动阈值分割和Top-Hat变换,得到纤维边缘和鳞片边缘.仿真结果表明,基于支持向量机的动物纤维图像识别率高于传统的基于人工神经网络的识别率.
|
| 关 键 词： | 支持向量机 增量学习算法 动物纤维 图像识别 |
| 文章编号： | 1006-5911(2003)S0-0144-05 |
An Incremental Learning Algorithm for Support Vector Machine and its Application |
| |
| ZENG Wen-hua. An Incremental Learning Algorithm for Support Vector Machine and its Application[J]. Computer Integrated Manufacturing Systems, 2003, 9(Z1): 144-148 |
| |
| Authors: | ZENG Wen-hua |
| |
| Affiliation: | ZENG Wen-hua~ |
| |
| Abstract: | In this paper we present a learning algorithm for incremental support vector machine (SVM). We analysis the possible changes of support vector set after new samples are added to training set. Based on the analysis result, an algorithm is presented. This algorithm is applied for the image recognition of two special animal fibers. With the algorithm, the useless sample is discarded and knowledge is accumulated. The experiment result shows that this algorithm is more effective than the traditional SVM while the classification precision is also guaranteed. |
| |
| Keywords: | support vector machine incremental learning algorithm animal fiber image recognition |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
|
