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 …

Aerial scene classification, which aims to automatically label an aerial image with a specific
semantic category, is a fundamental problem for understanding high-resolution remote …

Scene classification of remote sensing images has drawn great attention because of its wide
applications. In this paper, with the guidance of the human visual system (HVS), we explore …

Remote sensing image scene classification is one of the most challenging problems in
understanding high-resolution remote sensing images. Deep learning techniques …

We present an analysis of three possible strategies for exploiting the power of existing
convolutional neural networks (ConvNets or CNNs) in different scenarios from the ones they …

Remote sensing scene understanding is a highly challenging task, and has gradually
emerged as a research hotspot in the field of intelligent interpretation of remote sensing …

In this paper, we evaluate the generalization power of deep features (ConvNets) in two new
scenarios: aerial and remote sensing image classification. We evaluate experimentally …

Remote sensing image scene classification has attracted great attention because of its wide
applications. Although convolutional neural network (CNN)-based methods for scene …

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 …

The availability of high-resolution remote sensing (HRRS) data has opened up the
possibility for new interesting applications, such as per-pixel classification of individual …