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 …

Current deep-learning models are mostly built upon neural networks, ie multiple layers of
parameterized differentiable non-linear modules that can be trained by backpropagation. 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 …

In recent years visual place recognition (VPR), ie, the problem of recognizing the location of
images, has received considerable attention from multiple research communities, spanning …

Remote sensing (RS) image scene classification is an important research topic in the RS
community, which aims to assign the semantics to the land covers. Recently, due to the …

In recent years, convolutional neural network (CNN)-based methods have been widely used
for remote sensing (RS) scene classification tasks and have achieved excellent results …

Satellite image time series (SITS) classification is a major research topic in remote sensing
and is relevant for a wide range of applications. Deep learning approaches have been …

DEEP LEARNING FOR THE EARTH SCIENCES Explore this insightful treatment of deep
learning in the field of earth sciences, from four leading voices Deep learning is a …

The content-based remote sensing image retrieval (CBRSIR) has attracted increasing
attention with the number of remote sensing (RS) images growing explosively. Benefiting …