{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/deep-learning-in-remote-sensing-a-review","title":"Deep learning in remote sensing: a review","arxiv_id":"1710.03959","date":"2017-10-11","proceeding":null,"authors":["Xiao Xiang Zhu","Devis Tuia","Lichao Mou","Gui-Song Xia","Liangpei Zhang","Feng Xu","Friedrich Fraundorfer"],"abstract":"Standing at the paradigm shift towards data-intensive science, machine\nlearning techniques are becoming increasingly important. In particular, as a\nmajor breakthrough in the field, deep learning has proven as an extremely\npowerful tool in many fields. Shall we embrace deep learning as the key to all?\nOr, should we resist a 'black-box' solution? There are controversial opinions\nin the remote sensing community. In this article, we analyze the challenges of\nusing deep learning for remote sensing data analysis, review the recent\nadvances, and provide resources to make deep learning in remote sensing\nridiculously simple to start with. More importantly, we advocate remote sensing\nscientists to bring their expertise into deep learning, and use it as an\nimplicit general model to tackle unprecedented large-scale influential\nchallenges, such as climate change and urbanization.","url_abs":"http://arxiv.org/abs/1710.03959v1","url_pdf":"http://arxiv.org/pdf/1710.03959v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"deep-learning-in-remote-sensing-a-review","repo_url":"https://github.com/bluove/__DL-prediction-on-earth-phenology","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"deep-learning","task_name":"Deep Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}