In an image semantic annotation system, it often encounters the large-scale and high dimensional feature datasets problem, which leads to a slow learning process and degrading image semantic annotation accuracy. In order to reduce the high time complexity caused by redundancy information of image feature dataset, we adopt an improved affinity propagation (AP) algorithm to improve annotation by extracting and re-grouping the repeated feature points. The time consumption is reduced by square of repetition factor. The experiments results illustrate that the proposed annotation method has excellent time complexity and better annotation precision compared with original AP algorithms. © 2011 Springer-Verlag.
CITATION STYLE
Yang, D., & Guo, P. (2011). Performance analysis of improved affinity propagation algorithm for image semantic annotation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6676 LNCS, pp. 420–428). https://doi.org/10.1007/978-3-642-21090-7_50
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