The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
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X Demographics
Mendeley readers
| Title |
A field-based recommender system for crop disease detection using machine learning
|
|---|---|
| Published in |
Frontiers in Artificial Intelligence, April 2023
|
| DOI | 10.3389/frai.2023.1010804 |
| Pubmed ID | |
| Authors |
Jonathan Omara, Estefania Talavera, Daniel Otim, Dan Turcza, Emmanuel Ofumbi, Godliver Owomugisha |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Uganda | 2 | 25% |
| Netherlands | 1 | 13% |
| Switzerland | 1 | 13% |
| United States | 1 | 13% |
| Unknown | 3 | 38% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 75% |
| Scientists | 2 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 32 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 3 | 9% |
| Lecturer > Senior Lecturer | 1 | 3% |
| Librarian | 1 | 3% |
| Unspecified | 1 | 3% |
| Lecturer | 1 | 3% |
| Other | 3 | 9% |
| Unknown | 22 | 69% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 4 | 13% |
| Unspecified | 1 | 3% |
| Environmental Science | 1 | 3% |
| Arts and Humanities | 1 | 3% |
| Mathematics | 1 | 3% |
| Other | 3 | 9% |
| Unknown | 21 | 66% |