Deep convolutional neural networks (CNNs) have shown superior performance on the task
of single-label image classification. However, the applicability of CNNs to multi-label images …

Image annotation aims to annotate a given image with a variable number of class labels
corresponding to diverse visual concepts. In this paper, we address two main issues in large …

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 …

Multilabel image annotation attracts a lot of research interest due to its practicability in
multimedia and computer vision fields, while the need for a large amount of labeled training …

Every day, websites and personal archives generate an increasing number of photographs.
The extent of these archives is unfathomable. The ease of usage of these enormous digital …

Automatic image annotation methods are extremely beneficial for image search, retrieval,
and organization systems. The lack of strict correlation between semantic concepts and …

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 …

Nowadays, image annotation has attracted extensive attention due to the explosive growth
of image data. Large amount of researches on AIA have been proposed, mainly including …

Person search by natural language description is a challenging problem because of
demands for modelling and learning visual-text semantic embedding. While several works …

Funding agencies play a pivotal role in bolstering research endeavors by allocating financial
resources for data collection and analysis. However, the lack of detailed information …