Image similarity matching retrieval on synergetic neural network

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Abstract

In this paper, an image similarity matching retrieval algorithm based on synergetic neural network (SNN) is proposed. It is a novel method with advantages of no pseudo-state and closer to natural self-organization process in the field of image retrieval. It utilizes feature vector extraction, attention parameter selection, order parameter calculation, pseudo-inverse matrix and its determinant value comparison to achieve better retrieval effect. Due to the structural characteristic of synergetic neural network, it can save time for iteration and improve efficiency and speed. The experimental results show that this algorithm has fast speediness, strong robustness and high accuracy, and provides greater generality and high real-time performance. ©2010 IEEE.

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Li, H., Ma, X., Wan, W., & Zhou, X. (2010). Image similarity matching retrieval on synergetic neural network. In ICALIP 2010 - 2010 International Conference on Audio, Language and Image Processing, Proceedings (pp. 1566–1571). https://doi.org/10.1109/ICALIP.2010.5684499

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