Abstract
As a fundamental and important task in remote sensing, remote sensing image scene understanding (RSISU) has attracted tremendous research interest in recent years. RSISU includes the following sub-tasks: remote sensing image scene classification, remote sensing image scene retrieval, and scene-driven remote sensing image object detection. Although these sub-tasks have different goals, they share some communal hints. Hence, this paper tries to discuss them as a whole. Similar to other domains (e.g., speech recognition and natural image recognition), deep learning has also become the state-of-the-art technique in RSISU. To facilitate the sustainable progress of RSISU, this paper presents a comprehensive review of deep-learning-based RSISU methods, and points out some future research directions and potential applications of RSISU.
Highlights
With the advancement of remote sensing imaging technology, the spatial resolution of remote sensing images has been continuously improved
To achieve a collaborative development of remote sensing image scene classification, remote sensing image scene retrieval, and scene-driven geospatial object detection, this paper aims at summarizing the deep learning driven achievements around remote sensing image scene understanding (RSISU) and systematically depicting the relationship among the sub-tasks in RSISU
Content-based, rather than text-based remote sensing image implementation is what we focus on in this paper, which is achieved by calculating the similarity scene retrieval implementation is what we focus on in this paper, which is achieved by calculating the between visual features
Summary
With the advancement of remote sensing imaging technology, the spatial resolution of remote sensing images has been continuously improved. As the basic tasks of RSISU, remote sensing image scene classification, remote sensing image scene retrieval, and scene-driven geospatial object detection share some communal hints (e.g., scene abstraction) but have key respective techniques, as well as different goals. To achieve a collaborative development of remote sensing image scene classification, remote sensing image scene retrieval, and scene-driven geospatial object detection, this paper aims at summarizing the deep learning driven achievements around RSISU and systematically depicting the relationship among the sub-tasks in RSISU.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.