A survey on deep learning-driven remote sensing image scene understanding: Scene classification, scene retrieval and scene-guided object detection
As a fundamental and important task in remote sensing, remote sensing image scene
understanding (RSISU) has attracted tremendous research interest in recent years. RSISU …
understanding (RSISU) has attracted tremendous research interest in recent years. RSISU …
Remote sensing image retrieval in the past decade: Achievements, challenges, and future directions
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 …
from a large remote sensing image archive, which has remained to be a hot topic over the …
Depth image denoising using nuclear norm and learning graph model
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 …
it reflects the three-dimensional scene and can be applied in various fields of computer …
Image retrieval from remote sensing big data: A survey
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 …
increasing remote sensing imaging sensors on these platforms, has led to the formation of …
PatternNet: A benchmark dataset for performance evaluation of remote sensing image retrieval
Benchmark datasets are critical for developing, evaluating, and comparing remote sensing
image retrieval (RSIR) approaches. However, current benchmark datasets are deficient in …
image retrieval (RSIR) approaches. However, current benchmark datasets are deficient in …
Multilabel remote sensing image retrieval based on fully convolutional network
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 …
retrieval where each image is annotated by a single label representing the most significant …
Multilabel remote sensing image retrieval using a semisupervised graph-theoretic method
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 …
require a large number of already annotated images to train a classifier for obtaining high …
Siamese graph convolutional network for content based remote sensing image retrieval
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 …
resolution (VHR) remote sensing (RS) images using the notion of a novel Siamese graph …
Performance evaluation of single-label and multi-label remote sensing image retrieval using a dense labeling dataset
Benchmark datasets are essential for developing and evaluating remote sensing image
retrieval (RSIR) approaches. However, most of the existing datasets are single-labeled, with …
retrieval (RSIR) approaches. However, most of the existing datasets are single-labeled, with …
Toward remote sensing image retrieval under a deep image captioning perspective
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 …
capability of the extracted features in characterizing the semantic content of images. Existing …