In this paper, we propose a new image clustering algorithm, referred to as clustering using
local discriminant models and global integration (LDMGI). To deal with the data points …

In this paper, we present an image parsing to text description (I2T) framework that generates
text descriptions of image and video content based on image understanding. The proposed …

The Bag-of-Words (BoW) model is a promising image representation technique for image
categorization and annotation tasks. One critical limitation of existing BoW models is that …

Recent years have witnessed the great success of social media websites. Tag-based image
search is an important approach to accessing the image content on these websites …

Automatically assigning keywords to images is of great interest as it allows one to retrieve,
index, organize and understand large collections of image data. Many techniques have …

Automatically assigning relevant text keywords to images is an important problem. Many
algorithms have been proposed in the past decade and achieved good performance. Efforts …

A comprehensive survey on patch recognition, which is a crucial part of content-based
image retrieval (CBIR), is presented. CBIR can be viewed as a methodology in which three …

Multi-label problems arise in various domains such as multi-topic document categorization,
protein function prediction, and automatic image annotation. One natural way to deal with …

Purpose To develop a system to facilitate the retrieval of radiologic images that contain
similar-appearing lesions and to perform a preliminary evaluation of this system with a …

As the number of digital images is growing fast and Content-based Image Retrieval (CBIR)
is gaining in popularity, CBIR systems should leap towards Web-scale datasets. In this …