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Acknowledgment to Reviewers of Remote Sensing in 2021
Rigorous peer-reviews are the basis of high-quality academic publishing [...]
Remote Sensing Editorial Office
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In the original article [...]
Remote Sensing Editorial Office
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There was an error in the original publication [...]
Remote Sensing Editorial Office
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There was an error in the original publication [...]
Remote Sensing Editorial Office
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Deep learning in remote sensing: a review [PDF]
Standing at the paradigm shift towards data-intensive science, machine learning techniques are becoming increasingly important. In particular, as a major breakthrough in the field, deep learning has proven as an extremely powerful tool in many fields ...
Fraundorfer, Friedrich +6 more
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Announcement: Remote Sensing 2017 Best Guest Editor Award
Guest Editors help invite many high-quality papers for Remote Sensing[...]
Remote Sensing Office
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Announcement: Remote Sensing 2017 Best Reviewer Award Winners
Peer review is an essential part of the publication process, ensuring that Remote Sensing maintains the high standard of its published papers[...]
Remote Sensing Office
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Acknowledgment to Reviewers of Remote Sensing in 2020
Peer review is the driving force of journal development, and reviewers are gatekeepers who ensure that Remote Sensing maintains its standards for the high quality of its published papers [...]
Remote Sensing Editorial Office
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Acknowledgement to Reviewers of Remote Sensing in 2013
The publisher and editors of the Remote Sensing would like to express their sincere gratitude to the following reviewers for assessing manuscripts in 2013 for Remote Sensing.
Remote Sensing Editorial Office
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Acknowledgement to Reviewers of Remote Sensing in 2019
The editorial team greatly appreciates the reviewers who have dedicated their considerable time and expertise to the journal’s rigorous editorial process over the past 12 months, regardless of whether the papers are finally published or not.[...]
Remote Sensing Editorial Office
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