Cross-modal hashing plays a pivotal role in large-scale remote sensing (RS) ship image
retrieval. RS ship images often exhibit similar overall appearance with subtle differences …

Cross-modal hashing is an important tool for retrieving useful information from very-high-
resolution (VHR) optical images and synthetic aperture radar (SAR) images. Dealing with …

In recent years, cross-modal remote sensing image retrieval has attracted a lot of attention in
remote sensing (RS) information processing. It is worth mentioning that land cover scenes …

The retrieval of multimodal ship images obtained by remote sensing satellites is an
important content of remote sensing data analysis, which is of great significance to improve …

Cross-modal image retrieval has attracted much attention in remote sensing (RS) data
analysis these years, and however, the retrieval of target images, such as surface vessels …

Hashing retrieval is a widely used technique in high spatial resolution remote sensing (RS)
images due to its efficient retrieval speed and low memory overhead. However, existing …

Cross-modal hashing aims to retrieve similar images from large-scale Earth observation
(EO) data archives, which typically contain multiple satellite sources of remote sensing (RS) …

The amount of multi-modal data available on the Internet is enormous. Cross-modal hash
retrieval maps heterogeneous cross-modal data into a single Hamming space to offer fast …

Cross-modal hashing retrieval approaches maps heterogeneous multi-modal data into a
common hamming space to achieve efficient and flexible retrieval performance. However …

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 …