Remote sensing image retrieval (RSIR) aims to search and retrieve the images of interest
from a large remote sensing image archive, which has remained to be a hot topic over the …

In remote sensing field, the image retrieval is considered a complex task and attained higher
attention, because of the data acquired from the earth observation satellites. An …

For high-resolution remote sensing image retrieval tasks, single-scale features cannot fully
express the complexity of the image information. Due to the large volume of remote sensing …

In remote sensing (RS) community, RSIR (Remote Sensing Image Retrieval) is considered
as a tough topic and gained more attention because the data is collected via EO (Earth …

The increasing volume of high-resolution satellite imagery made image retrieval a
demanding research field in the remote sensing (RS) community. The RS data are often …

ABSTRACT A considerable volume of high-resolution remote sensing (HRRS) data is
generated with the intense space explorations happening globally. Remote sensing image …

Now a days, Remote Sensing (RS) techniques are used for earth observation and for
detection of soil types with high accuracy and better reliability. This technique provides …

Detecting oriented small objects is a critical task in remote sensing, but the development of
high-performance deep learning-based detectors is hindered by the need for large-scale …

Wetlands, situated at the vital intersection of terrestrial and aquatic ecosystems, are pivotal
in preserving global biodiversity and maintaining environmental equilibrium. The escalating …

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 …