Abstract
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.
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Yang, D., Guo, P. (2011). Performance Analysis of Improved Affinity Propagation Algorithm for Image Semantic Annotation. In: Liu, D., Zhang, H., Polycarpou, M., Alippi, C., He, H. (eds) Advances in Neural Networks – ISNN 2011. ISNN 2011. Lecture Notes in Computer Science, vol 6676. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21090-7_50
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DOI: https://doi.org/10.1007/978-3-642-21090-7_50
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