The Research on Algorithms of Relevance Feedback(RF) and Classification in Image Retrieval 图像检索中的相关反馈和分类算法研究
Data fusion and relevance feedback based query expansion are two effective methods for information retrieval optimizing. 数据融合和基于相关度反馈的查询扩展是两种有效的检索过程优化技术。
Research on 3D Model Retrieval System Based on Multi-feature and Relevance Feedback(RF) 基于多特征和相关反馈的三维模型检索系统研究与实现
The algorithm combines active learning, biased classification and incremental learning to model the small sample biased learning problem in relevance feedback process. 该算法将主动式学习、有偏分类和增量学习结合起来,对相关反馈过程中的小样本有偏学习问题进行建模。
Method of Image Retrieval Based on Integrating Low Level Feature with Relevance Feedback(RF) 基于综合特征和相关反馈的图像检索方法研究