Jun 9, 2011 · In this paper, we propose a new bag-based reranking framework for large-scale TBIR. Specifically, we first cluster relevant images using both ...

To improve retrieval performance, in this paper we introduce a new framework, referred to as the bag-based image re- ranking framework, for large-scale TBIR. We ...

Abstract: Nowadays, web-scale image search engines (e.g. Google Image Search, Microsoft Live Image. Search) rely almost purely on surrounding text features.

Image search re-ranking aims to reorder image results based on multimodal cues, which may be specific visual patterns from the ini- tial search results or ...

Bibliographic details on Improving Web Image Search by Bag-Based Reranking.

May 12, 2013 · Final Year Projects | Improving Web Image Search by Bag-Based Reranking More Details: Visit ...

we propose a new methodology that will classify the whole dataset and also the given query image. By doing so we can reduce the similarity searching time.

Online image re- ranking has been shown to be an effective way to improve the image search results [2]. Partition the relevant images into clusters by using ...

Jan 17, 2021 · Image re-ranking, as an effective way to improve the results of web-based image search, has been adopted by current commercial search engines.

Abstract- Image re-ranking is, the easiest way to improve the performance of web-based image search and it is used by the various search engine .