mlsanityData to 7 Oct 2026

An Improved Relevance Feedback in CBIR

arXiv 2006.11821 ↗First posted 21 Jun 2020cs.IR stat.MLcited by 1

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Abstract (arXiv)

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.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). First posted on arXiv 21 Jun 2020.

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