Hashing methods have been extensively applied to efficient multimedia data indexing and
retrieval on account of the explosion of multimedia data. Cross-modal hashing usually …

Learning-based hashing algorithms are “hot topics” because they can greatly increase the
scale at which existing methods operate. In this paper, we propose a new learning-based …

With explosive growth of data volume and ever-increasing diversity of data modalities, cross-
modal similarity search, which conducts nearest neighbor search across different modalities …

Hash coding has been widely used in the approximate nearest neighbor search for large-
scale image retrieval. Recently, many deep hashing methods have been proposed and …

Compact hash code learning has been widely applied to fast similarity search owing to its
significantly reduced storage and highly efficient query speed. However, it is still a …

Semantic-preserving hashing establishes efficient multimedia retrieval by transferring
knowledge from original data to hash codes so that the latter can preserve the underlying …

Hashing has been widely used for large-scale approximate nearest neighbor search due to
its storage and search efficiency. Recent supervised hashing research has shown that deep …

Completely automated iris recognition has emerged as an integral part of e-business and e-
governance infrastructure which has acquired billions of iris images under near-infrared …

Hashing has been widely applied to multimodal retrieval on large-scale multimedia data due
to its efficiency in computation and storage. In this article, we propose a novel deep semantic …

Driven by the urgent demand for managing remote sensing big data, large-scale remote
sensing image retrieval (RSIR) attracts increasing attention in the remote sensing field. In …