# An Improved Relevance Feedback in CBIR

arXiv: https://arxiv.org/abs/2006.11821 · HTML: https://mlsanity.com/paper/2006.11821/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Jun 2020.

## Built on by (most cited first, 1 of 1)

- [Advancements in Content-Based Image Retrieval: A Comprehensive Survey of Relevance Feedback Techniques](https://mlsanity.com/paper/2312.10089/) (2023)

## 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.