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Visual query processing for efficient image retrieval using a SOM-based filter-refinement scheme. Presenter : JHOU, YU-LIANG Authors : Zhiwen Yu, Hau -San Wong, Jane You, Guoqiang Han 2012,Information Sciences. Outlines. Motivation Objectives Methodology
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Visual query processing for efficient image retrieval using a SOM-based filter-refinement scheme Presenter : JHOU, YU-LIANGAuthors : Zhiwen Yu, Hau-San Wong, Jane You, Guoqiang Han2012,Information Sciences
Outlines • Motivation • Objectives • Methodology • Experiments • Conclusions • Comments
Motivation • Content-based image retrieval is one of the most effective ways of retrieving visual data. • However, When a large number of pictures the relevance feedback process is a tedious and time consuming and requires high computational cost.
Objectives • To make the query process more robust. • To make image retrieval more intuitive and effective.
Methodologylocal membership function the neuron is in a d-level local neighborhood (ii) the distance between the weight vector of the neuron and the input vector is not greater than the s-th smallest distance among all the distances between the input vector and the weight vectors of the neurons in the neighborhood
Experimental setting (i) the feature vectors of the query images are identical distributed is denoted as AVAC (i) (ii) the feature vectors of the query images are randomly distributed is denoted as AVAC (r)
Conclusions • We adopt our new approach can improve the accuracyand efficiency of the process.
Comments • Advantages More accuracyand efficiency. Applications -Self organizing map -Image retrieval