Refereed full papers (journals, book chapters, international conferences)

2003

@article{ZTI2003,
	vgclass =	{refpap},
	author =	{Tong Zhao and Lilian H. Tang and Horace H. S. Ip and Feihu
	Qi},
	title =	{On relevance feedback and similarity measure for image
	retrieval with synergetic neural nets},
	journal =	{Neurocomputing},
	volume =	{51},
	pages =	{105--124},
	month =	{April},
	year =	{2003},
	url =	{http://dx.doi.org/10.1016/S0925-2312(02)00604-5},
	abstract =	{In image retrieval, research issues relating to the design
	of a similarity function, which corresponds to human perception, remain
	open. Here we exploit a new interpretation of the control parameter,
	\emph{order vector}, used in synergetic neural net (SNN) and use it as
	the basis of a similarity function for shape-based retrieval. More
	specifically, we have proven certain properties and theorems which give
	a formal basis for SNN based image retrieval. Based on the properties,
	an efficient affine invariant similarity measure has been developed for
	trademark images. Furthermore, we propose a self-attentive retrieval
	and relevance feedback mechanism for similarity measure refinement.
	Experiments also demonstrated that the proposed similarity measure is
	able to reflect the user's view of similarity through relevance
	feedback which in turn reinforces the retrieval ranking.},
}