• MANUPATI PALLA RAO
• A. DURGA DEVI

As the image sharing websites like Flickr become more and more popular, extensive scholars concentrate on tag-based image retrieval (TBIR). It is one of the important ways to find images contributed by social users. In this research field, tag information and diverse visual features have been investigated. However, most existing methods use these visual features separately for tagging the images. In this proposed work, we propose a global and local visual features fusion approach to learn the relevance of images by hypergraph approach. A hypergraph is constructed first by utilizing global, local visual features and tag information.

JOINT HYPERGRAPH LEARNING FOR TAG BASED IMAGE RETRIEVAL

"JOINT HYPERGRAPH LEARNING FOR TAG BASED IMAGE RETRIEVAL", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 7, page no.g585-g596, July-2021, Available :http://www.jetir.org/papers/JETIR2107806.pdf

"JOINT HYPERGRAPH LEARNING FOR TAG BASED IMAGE RETRIEVAL", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 7, page no. ppg585-g596, July-2021, Available at : http://www.jetir.org/papers/JETIR2107806.pdf