Yen-Ren Huang

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A general spatial similarity ranking framework between two symbolic images with multiple pairwise spatial relations is proposed. The degree of similarity between two spatial relations is mapped to the distance between the associated nodes in an Interval Neighbor Group. The shorter the distance, the higher degree of similarity, while a longer one, a lower(More)
The EM (expectation-maximization) algorithm is a broadly applicable method for calculating maximum likelihood estimates given incomplete data [1]. EM algorithms have received considerable attention due to their computation feasibility in tomographic image reconstruction [2~4], symbol detection [5] and parameter estimation [6]. However, it is less recognized(More)
In this paper, a multiple-instance image retrieval system incorporating a general spatial similarity measure is proposed. A multiple-instance learning is employed to summarize the commonality of spatial features among positive and negative example images. The general spatial similarity measure evaluates the degree of similarity between matching atomic(More)
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