In recent years, image annotation has attracted extensive attention due to the explosive
growth of image data. With the capability of describing images at the semantic level, image …

In the current era of digital communication, the use of images is growing exponentially since
they are one of the best ways of expressing, sharing and memorizing knowledge. In fact …

Image tag recommendation, aiming at assigning a set of relevant tags for images, is a useful
way to help users organize images' content. Early methods in image tagging mainly …

Recent studies have shown that sparse representation (SR) can deal well with many
computer vision problems, and its kernel version has powerful classification capability. In …

Automatic image annotation is one of the research fields helping to extract the meaning of
images, which aims at the production of a set of semantic annotations for an image to help …

Automatic image annotation (AIA) for a wide-range collection of image data is a difficult
challenging topic and has attracted the interest of many researchers in the last decade. To …

This paper proposes a new and effective framework for color image retrieval based on Full
Range Autoregressive Model (FRAR). Bayesian approach (BA) is used to estimate the …

Graph-based algorithms are known to be effective approaches to semi-supervised learning.
However, there has been relatively little work on extending these algorithms to the multi …

Online images' tags are very important for indexing, sharing, and searching of images, as
well as surfacing images with private or sensitive content, which needs to be protected …

Image automatic annotation is a significant and challenging problem in pattern recognition
and computer vision. Current image annotation models almost used all the training images …