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 …

We propose simple and effective models for the image annotation that make use of
Convolutional Neural Network (CNN) features extracted from an image and word …

Image annotation has attracted a lot of research interest, and multi-label learning is an
effective technique for image annotation. How to effectively exploit the underlying correlation …

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 …

Automatic image annotation aims at predicting a set of semantic labels for an image.
Because of large annotation vocabulary, there exist large variations in the number of images …

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 …

Nowadays, image annotation has been a hot topic in the semantic retrieval field due to the
abundant growth of digital images. The purpose of these methods is to realize the content of …

The rapid growth of archives of available visual content, such as photo or video sharing
websites, has created a need for indexing techniques and multimedia information search …

Abstract Automatic Image Annotation (AIA) helps image retrieval systems by predicting tags
for images. In this paper, we propose an AIA system using Non-negative Matrix Factorization …

Automatic image annotation (AIA) is a mechanism for describing the visual content of an
image with a list of semantic labels. Typically, there is a massive imbalance between …