Remote sensing image scene classification with deep learning (DL) is a rapidly growing
field that has gained significant attention in the past few years. While previous review papers …

Remote sensing image scene classification, which aims at labeling remote sensing images
with a set of semantic categories based on their contents, has broad applications in a range …

Since last decade, deep learning has made exceptional progress in various fields of artificial
intelligence including image and voice recognition, natural language processing. Inspired …

The recent emergence of deep learning for characterizing complex patterns in remote
sensing imagery reveals its high potential to address some classic challenges in this …

Classifying different satellite remote sensing scenes is a very important subtask in the field of
remote sensing image interpretation. With the recent development of convolutional neural …

Remote sensing image scene classification plays an important role in a wide range of
applications and hence has been receiving remarkable attention. During the past years …

Remote sensing image scene classification (RSISC) is an active task in the remote sensing
community and has attracted great attention due to its wide applications. Recently, the deep …

Learning powerful discriminative features is the key for remote sensing scene classification.
Most existing approaches based on convolutional neural network (CNN) have achieved …

Remote sensing image scene classification, which aims to identify the types of land cover, is
a fundamental task in remote sensing image analysis. Remote sensing images contain a …

Recently, remote sensing image scene classification technology has been widely applied in
many applicable industries. As a result, several remote sensing image scene classification …