Deep hashing has been widely used for large-scale cross-modal retrieval benefited from the
low storage cost and fast search speed. However, most existing deep supervised methods …

Due to the storage and retrieval efficiency of hashing, as well as the highly discriminative
feature extraction by deep neural networks, deep cross-modal hashing retrieval has been …

Watermarking is an effective solution for copyright protection and forensics tracking via
hiding information into the image signal. Recently, spatial-embedding watermarking …

Supervised cross-modal retrieval has significant advantages in retrieval efficiency and
storage cost. In the field of hashing retrieval, existing supervised methods are divided into …

With an emphasis on saving storage and computation costs, hashing learning has got
considerable success in cross-modal image retrieval. Most pioneer efforts in this direction …

Along with the continuous breakthrough and popularization of information network
technology, multi-modal data, including texts, images, videos, and audio, is growing rapidly …

In recent years, the transformation of devices and systems into intelligent, interconnected
entities has given rise to the concepts widely recognized as the Internet of Things (IoT) and …

To overcome the barrier of storage and computation, the hashing technique has been widely
used for nearest neighbor search in multimedia retrieval applications recently. Particularly …

In response to the problem of similarity measure differences in different similarity coefficients
that occur in cross-modal multi-label retrieval, this article uses an interval parameter to …

Existing cross-media retrieval approaches usually project low-level features from different
modalities of data into a common subspace, in which the similarity of multi-modal data can …