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《Computer Science》 2010-07
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Semi-supervised Feedback Algorithm Based on Locally Adaptive Approximation

HUANG Chuan-bo1 XIANG Li2 JIN Zhong1 (Department of Computer Science,Nanjing University of Science and Technology,Nanjing 210094,China)1 (Film&Media Academy,Chongqing Normal University,Chongqing 400047,China)2  
In this paper,identification information was put into the distance measure,using this new distance measure instead of the Euclidean distance to construct k-neighbor,we proposed a new local linear nearest neighborhood propagation method.This provides a semi-supervised feedback algorithm based on the local adaptive approximation for image retrieval relevance feedback mechanism FLANNP (feedback locally adaptive nearest neighbor propagation).The decision function constructed by SVMs was used to determine the most discriminant direction in a neighborhood around the query.Such a direction provides a local adaptive distance algorithm.By this the reconstruction weights were computed.After all the labels were propagated from the labeled points to the whole dataset using the local linear neighborhoods with sufficient smoothness.The approach makes use of identification information in distance measure and improves the accuracy of image retrieval.
【Fund】: 国家863高技术研究发展计划(No.2006AA01Z119);; 国家自然科学基金(No.60473039)资助
【CateGory Index】: TP181
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