  Relevance Feedback in Content-Based Image Retrieval is a method where the
feedback of the performance is being used to improve itself. Prior works use
feature re-weighting and classification techniques as the Relevance Feedback
methods. This paper shows a novel addition to the prior methods to further
improve the retrieval accuracy. In addition to all of these, the paper also
shows a novel idea to even improve the 0-th iteration retrieval accuracy from
the information of Relevance Feedback.
