Cross-modal hashing has sparked much attention in large-scale information retrieval for its
storage and query efficiency. Despite the great success achieved by supervised …

In the recent digitization era, image hashing is a key technology, including image
recognition, authentication and manipulation detection, among many multimedia security …

With the growing amount of multimodal data, cross-modal retrieval has attracted more and
more attention and become a hot research topic. To date, most of the existing techniques …

Due to its powerful capability of representation learning and high-efficiency computation,
deep hashing has made significant progress in large-scale image retrieval. However, deep …

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

Content-based histopathology image retrieval can be a useful technique for help in
diagnosing various diseases. The process of retrieving images is often time-consuming and …

In light of the ability to enable efficient storage and fast query for big data, hashing
techniques for cross-modal search have aroused extensive attention. Despite the great …

The most striking success of deep hashing for large-scale image retrieval benefits from its
powerful discriminative representation of deep learning and the attractive computational …

Deep hashing integrates the advantages of deep learning and hashing technology, and has
become the mainstream of the large-scale image retrieval field. However, when training the …

The cross-modal retrieval task has raised continuous attention in recent years with the
increasing scale of multi-modal data, which has broad application prospects including …