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Timeline
X Demographics
Mendeley readers
Title |
Assessment of a Spatiotemporal Deep Learning Approach for Soil Moisture Prediction and Filling the Gaps in Between Soil Moisture Observations
|
---|---|
Published in |
Frontiers in Artificial Intelligence, March 2021
|
DOI | 10.3389/frai.2021.636234 |
Pubmed ID | |
Authors |
Mohamed ElSaadani, Emad Habib, Ahmed M. Abdelhameed, Magdy Bayoumi |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Saudi Arabia | 1 | 50% |
Switzerland | 1 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 1 | 50% |
Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 59 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 9 | 15% |
Student > Master | 7 | 12% |
Researcher | 7 | 12% |
Student > Doctoral Student | 5 | 8% |
Lecturer | 4 | 7% |
Other | 6 | 10% |
Unknown | 21 | 36% |
Readers by discipline | Count | As % |
---|---|---|
Engineering | 13 | 22% |
Environmental Science | 7 | 12% |
Earth and Planetary Sciences | 5 | 8% |
Computer Science | 4 | 7% |
Unspecified | 3 | 5% |
Other | 3 | 5% |
Unknown | 24 | 41% |