Add to ORKGSearching for relevant images given a query term is an important task in nowadays large-scale community databases. The image ranking approach presented in this work represents an image collection as a graph that is built using a multimodal similarity measure based on visual features and user tags. We perform a random walk on this graph to find the most common images. Further we discuss several scalability issues of the proposed approach and show how in this framework queries can be answered fast. Experimental results validate the effectiveness of the presented algorithm
In recent years, there has been a growing interest in developing effective methods for searching lar...
We propose a novel image representation, termed Attribute-Graph, to rank images by their semantic si...
The growing importance of traditional text-based image retrieval is due to its popularity through we...
In this work, four major components of image database have been examined: image similarity, search-b...
In this paper, we consider the problem of clustering and re-ranking web image search results so as t...
This paper introduces a web image search reranking approach that explores multiple modalities in a g...
Nowadays, large-scale networked social media need bet-ter search technologies to achieve suitable pe...
We propose a method to handle approximate searching by image content in large image databases. Image...
Users of image retrieval systems often find it frustrating that the image they are looking for is no...
Social media websites such as Flickr and Facebook are pervading our lives today. Thesefast-evolving ...
Indexing quickly and accurately in a large collection of images has become an important problem with...
Users of image retrieval systems often find it frustrating that the image they are looking for is no...
This work studies a new approach for image retrieval on largescale community databases. Our proposed...
Ranking on image search has attracted considerable attentions. Many graph-based algorithms have been...
This work aims at organizing the results of query-by-example image database management system so tha...
In recent years, there has been a growing interest in developing effective methods for searching lar...
We propose a novel image representation, termed Attribute-Graph, to rank images by their semantic si...
The growing importance of traditional text-based image retrieval is due to its popularity through we...
In this work, four major components of image database have been examined: image similarity, search-b...
In this paper, we consider the problem of clustering and re-ranking web image search results so as t...
This paper introduces a web image search reranking approach that explores multiple modalities in a g...
Nowadays, large-scale networked social media need bet-ter search technologies to achieve suitable pe...
We propose a method to handle approximate searching by image content in large image databases. Image...
Users of image retrieval systems often find it frustrating that the image they are looking for is no...
Social media websites such as Flickr and Facebook are pervading our lives today. Thesefast-evolving ...
Indexing quickly and accurately in a large collection of images has become an important problem with...
Users of image retrieval systems often find it frustrating that the image they are looking for is no...
This work studies a new approach for image retrieval on largescale community databases. Our proposed...
Ranking on image search has attracted considerable attentions. Many graph-based algorithms have been...
This work aims at organizing the results of query-by-example image database management system so tha...
In recent years, there has been a growing interest in developing effective methods for searching lar...
We propose a novel image representation, termed Attribute-Graph, to rank images by their semantic si...
The growing importance of traditional text-based image retrieval is due to its popularity through we...