Along with the explosive growth of multimedia data, automatic multimedia tagging has
attracted great interest of various research communities, such as computer vision …

While deep convolutional neural networks (CNNs) have shown a great success in single-
label image classification, it is important to note that most real world images contain multiple …

To achieve automatic recommendation of privacy settings for image sharing, a new tool
called iPrivacy (image privacy) is developed for releasing the burden from users on setting …

Deep convolution neural networks (CNNs) have demonstrated advanced performance on
single-label image classification, and various progress also has been made to apply CNN …

Graph-based semisupervised learning (GSSL) provides a promising paradigm for modeling
the manifold structures that may exist in massive data sources in high-dimensional spaces. It …

Large-scale user contributed images with tags are easily available on photo sharing
websites. However, the noisy or incomplete correspondence between the images and tags …

In this paper, each image is viewed as a bag of local regions, as well as it is investigated
globally. A novel method is developed for achieving multi-label multi-instance image …

In this paper, we present a novel method for image annotation and made three contributions.
Firstly, we propose to use the tags contained in the training images as the supervising …

We introduce in this paper a novel image annotation approach based on maximum margin
classification and a new class of kernels. The method goes beyond the naive use of existing …

In this work, we propose a weakly supervised graph propagation method to automatically
assign the annotated labels at image level to those contextually derived semantic regions …