Semi-supervision and Active Relevance Feedback Algorithm for Content-Based Image Retrieval
YE Shao-zhen · Computer Engineering and Applications Journal · 2006
To improve the efficiency of relevance feedback in image retrieval,a novel active learning algorithm SVMpr based on relevance probability is proposed in the paper.And combined with a semi-supervision learning, the framework of image retrieval based on semi-supervision and active learning is designed.In the process of relevance feedback, firstly, the labeled samples are trained by TSVM,secondly according to active learning algorithm in this paper,the k image samples from the unlabeled images are selected into the user which is added label and more helpful for useful sam-ples.Experimental result shows that the algorithm is better than traditional one,which is in improving significantly the efficiency and convergent rate of machine learning.