Image similarity matching retrieval on synergetic neural network

Audio Language and Image Processing(2010)

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摘要
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.
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关键词
natural self-organization process,feature vector extraction,image matching,matrix algebra,pseudo inverse matrix,image similarity matching retrieval,determinant value comparison,feature extraction,image retrieval,attention parameter selection,synergetic neural network,order parameter calculation,neural nets,pattern recognition,real time,accuracy,euclidean distance,vectors,feature vector,self organization,neural network,artificial neural networks,prototypes
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