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 …

Scene classification is a highly useful task in Remote Sensing (RS) applications. Many
efforts have been made to improve the accuracy of RS scene classification. Scene …

Hyperspectral image classification (HSIC) methods based on convolutional neural network
(CNN) continue to progress in recent years. However, high complexity, information …

Remote sensing scene classification (RSSC) is a hotspot and play very important role in the
field of remote sensing image interpretation in recent years. With the recent development of …

Scene classification of high spatial resolution (HSR) images can provide data support for
many practical applications, such as land planning and utilization, and it has been a crucial …

Scene classification is an indispensable part of remote sensing image interpretation, and
various convolutional neural network (CNN)-based methods have been explored to improve …

Scene classification is an active research topic in the remote sensing community, and
complex spatial layouts with various types of objects bring huge challenges to classification …

Remote sensing scene categorization (RSSC) is a long-standing, vital, and complex issue in
computer vision. It seeks to classify a scene into one of the predetermined scene groups by …

The scene classification of high spatial resolution (HSR) images is a challenging task in the
remote sensing community. How to construct a discriminative representation of the HSR …

Classification of the very high-resolution (VHR) imagery scene has become a challenging
problem. The convolutional neural network (CNN) has increased the accuracy in this area …