Artificial intelligence (AI) plays a growing role in remote sensing (RS). Applications of AI,
particularly machine learning algorithms, range from initial image processing to high-level …

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 …

In recent years, remote-sensing scene classification is one of the research hotspots and has
played an important role in the field of intelligent interpretation of remote-sensing data …

Deep convolutional neural networks have achieved competitive performance in salient
object detection, in which how to learn effective and comprehensive features plays a critical …

As an essential problem in computer vision, salient object detection (SOD) has attracted an
increasing amount of research attention over the years. Recent advances in SOD are …

Deep learning, which is a subfield of machine learning, has opened a new era for the
development of neural networks. The auto-encoder is a key component of deep structure …

Remote sensing image scene classification is an active and challenging task driven by
many applications. More recently, with the advances of deep learning models especially …

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

Deep learning (DL) is a powerful state-of-the-art technique for image processing including
remote sensing (RS) images. This letter describes a multilevel DL architecture that targets …