Effective disaster response is critical for communities to remain resilient and advance the
development of smart cities. Responders and decision-makers would benefit from reliable …

Remote sensing cross-modal text–image retrieval (RSCTIR) is a flexible and human-
centered approach to retrieving rich information from different modalities, which has …

With the explosion in the volume of collected high-resolution aerial image data, the
development of effective image retrieval methods for remote sensing (RS) has become a …

Remote sensing is a long-distance measuring technology that obtains data about a
phenomenon or an object. Remote sensing technology plays a crucial role in several …

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 …

The degradation of visual quality in remote sensing images caused by haze presents
significant challenges in interpreting and extracting essential information. To effectively …

This work introduces composed image retrieval to remote sensing. It allows to query a large
image archive by image examples alternated by a textual description, enriching the …

Content-Based Remote Sensing Image Retrieval (CBRSIR) is used to find relevant images
from large collections of remote sensing images. CBRSIR works by indexing each image in …

This paper proposed a novel texture feature extraction technique for radar remote sensing
image retrieval application using adaptive tetrolet transform and Gray level co-occurrence …

Most of existing studies regarding cross-modal content-based remote sensing image
retrieval (CM-CBRSIR) focus on reducing/enlarging the Euclidean distances of cross modal …