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Transformers in Remote Sensing: A Survey [PDF]

Remote Sensing, 2022
Deep learning-based algorithms have seen a massive popularity in different areas of remote sensing image analysis over the past decade. Recently, transformer-based architectures, originally introduced in natural language processing, have pervaded ...
Abdulaziz Amer Aleissaee, Amandeep Kumar, R. Anwer, Salman H. Khan, Hisham Cholakkal, Guisong Xia, F. Khan   +6 more
semanticscholar   +1 more source

Announcement: Remote Sensing 2017 Best Reviewer Award Winners

Remote Sensing, 2018
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
doaj   +1 more source

Remote Sensing for Biodiversity [PDF]

, 2016
Remote sensing (RS)---taking images or other measurements of Earth from above---provides a unique perspective on what is happening on the Earth and thus plays a special role in biodiversity and conservation applications. The periodic repeat coverage of satellite-based RS is particularly useful for monitoring change and so is essential for understanding
Matthew Colloff, Craig James, Erin L. Hestir, Andrew K. Skidmore, Patrick N. Halpin, Kristen J. Williams, Maria José Santos, Ned Horning, Gary N. Geller, Mary E. Blair, Nancy Aguirre, Steven R. Schill, Elizabeth J. Botha, William Magnusson, Brian Helmuth, Michael Abrams, Terry Dawson, Janet Franklin   +17 more
openaire   +6 more sources

Editorial: Remote Sensing for Aquaculture [PDF]

Frontiers in Marine Science, 2021
International ...
Gernez, Pierre, Palmer, Stephanie, Thomas, Yoann, Forster, Rodney   +3 more
openaire   +7 more sources

Acknowledgement to Reviewers of Remote Sensing in 2017

Remote Sensing, 2018
Peer review is an essential part in the publication process, ensuring that Remote Sensing maintains high quality standards for its published papers.[...]
Remote Sensing Editorial Office
doaj   +1 more source

Acknowledgment to Reviewers of Remote Sensing in 2020

Remote Sensing, 2021
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
doaj   +1 more source

Acknowledgement to Reviewers of Remote Sensing in 2013

Remote Sensing, 2014
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
doaj   +1 more source

Acknowledgement to Reviewers of Remote Sensing in 2019

Remote Sensing, 2020
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
doaj   +1 more source

Acknowledgment to the Reviewers of Remote Sensing in 2022

Remote Sensing, 2023
High-quality academic publishing is built on rigorous peer review [...]
Remote Sensing Editorial Office
doaj   +1 more source

RSMamba: Remote Sensing Image Classification With State Space Model [PDF]

IEEE Geoscience and Remote Sensing Letters
Remote sensing image classification forms the foundation of various understanding tasks, serving a crucial function in remote sensing image interpretation.
Keyan Chen, Bo-Ying Chen, Chenyang Liu, Wenyuan Li, Zhengxia Zou, Z. Shi   +5 more
semanticscholar   +1 more source