We present a Bayesian framework for content-based image retrieval which models the distribution of color and texture features within sets of related images. Given a userspecified ...
Abstract—Feature extraction is a key issue in contentbased image retrieval (CBIR). In the past, a number of texture features have been proposed in literature, including statistic...
Automatic image annotation has been an active research topic due to its great importance in image retrieval and management. However, results of the state-of-the-art image annotati...
Changhu Wang, Feng Jing, Lei Zhang, Hong-Jiang Zha...
Abstract. In this paper, the Ssair (Semi-Supervised Active Image Retrieval) approach, which attempts to exploit unlabeled data to improve the performance of content-based image ret...
—We present an image retrieval system based on a combined search of text and content. The idea is to use the text present in title, description, and tags of the images for improv...
Juan Manuel Barrios, Diego Diaz-Espinoza, Benjamin...