The traditional production paradigm of large batch production does not offer flexibility toward
satisfying the requirements of individual customers. A new generation of smart factories is …

Multimedia retrieval plays an indispensable role in big data utilization. Past efforts mainly
focused on single-media retrieval. However, the requirements of users are highly flexible …

Machine learning methods have achieved good performance and been widely applied in
various real-world applications. They can learn the model adaptively and be better fit for …

Cross-modal retrieval has become a highlighted research topic for retrieval across
multimedia data such as image and text. A two-stage learning framework is widely adopted …

The understanding of web images has been a hot research topic in both artificial intelligence
and multimedia content analysis domains. The web images are composed of various …

Hashing has recently sparked a great revolution in cross-modal retrieval because of its low
storage cost and high query speed. Recent cross-modal hashing methods often learn …

Cross-modal retrieval takes one type of data as the query to retrieve relevant data of another
type. Most of existing cross-modal retrieval approaches were proposed to learn a common …

In order to exploit the abundant potential information of the unlabeled data and contribute to
analyzing the correlation among heterogeneous data, we propose the semi-supervised …

Although there is a long line of research on bidirectional image–text matching, the problem
remains a challenge due to the well-known semantic gap between visual and textual …

With the dramatic increase in the amount of multimedia data, cross-modal similarity retrieval
has become one of the most popular yet challenging problems. Hashing offers a promising …