… With the success of deep learning methods in the field of computer vision, researchers have
… remote sensing image analysis. This paper starts with a summary of the fundamental deep …

… DL is also taking off in remote sensing image classification most recently, and a growing …
-wise and scene-wise remote sensing image classification approaches that are based on DL…

… two deep-learning frameworks that carry out ocean remote-sensing image classification and
… remote-sensing imagery to show how effective these deep-learning frameworks are (Fig. 1). …

… deep learning (MDL) framework. In particular, we also investigate a special case of multi-modality
learning (MML)—cross-modality learning (CML) that exists widely in RS image …

… We propose to use the Digital Imaging and Remote Sensing Image Generation (DIRSIG) …
We then capture synthetic aerial images of the scene with a MSI sensor model. We use the …

… of deep learning based on CNNs for remote sensing picture … , as well as data for remote
sensing image categorization and … As a result of the survey, we expect remote sensing scientists …

… Deep learning (DL) algorithms have seen a massive rise in popularity for remote-sensing
image analysis over the past few years. In this study, the major DL concepts pertinent to remote…

… In this paper, a new deep neural network of image semantic … remote sensing image must
to be clipped to train the deep … road extraction from remote sensing imagery, this work was …

… images is still lacking. Considering the rapid evolution of this field, this article provides a
systematic survey of deep learning methods for remote sensing image … of remote sensing image …

… deep learning (DL) approach to support automatic detection of terrain features from remotely
sensed images… 12,000 remotely sensed images (1,000 original images and 11,000 derived …