As a fundamental and important task in remote sensing, remote sensing image scene
understanding (RSISU) has attracted tremendous research interest in recent years. RSISU …

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 …

Depth image denoising is increasingly becoming the hot research topic nowadays, because
it reflects the three-dimensional scene and can be applied in various fields of computer …

Benchmark datasets are critical for develo**, evaluating, and comparing remote sensing
image retrieval (RSIR) approaches. However, current benchmark datasets are deficient in …

The blooming proliferation of aeronautics and astronautics platforms, together with the ever-
increasing remote sensing imaging sensors on these platforms, has led to the formation of …

Conventional remote sensing image retrieval (RSIR) system usually performs single-label
retrieval where each image is annotated by a single label representing the most significant …

Conventional supervised content-based remote sensing (RS) image retrieval systems
require a large number of already annotated images to train a classifier for obtaining high …

This paper deals with the problem of content-based image retrieval (CBIR) of very high
resolution (VHR) remote sensing (RS) images using the notion of a novel Siamese graph …

Benchmark datasets are essential for develo** and evaluating remote sensing image
retrieval (RSIR) approaches. However, most of the existing datasets are single-labeled, with …

The performance of remote sensing image retrieval (RSIR) systems depends on the
capability of the extracted features in characterizing the semantic content of images. Existing …