| Title |
Automatic analysis of social media images to identify disaster type and infer appropriate emergency response
|
|---|---|
| Published in |
Journal of Big Data, June 2021
|
| DOI | 10.1186/s40537-021-00471-5 |
| Authors |
Amna Asif, Shaheen Khatoon, Md Maruf Hasan, Majed A. Alshamari, Sherif Abdou, Khaled Mostafa Elsayed, Mohsen Rashwan |
Mendeley readers
The data shown below were compiled from readership statistics for 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 58 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 12% |
| Student > Master | 5 | 9% |
| Professor | 4 | 7% |
| Student > Doctoral Student | 3 | 5% |
| Professor > Associate Professor | 3 | 5% |
| Other | 10 | 17% |
| Unknown | 26 | 45% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 9 | 16% |
| Engineering | 8 | 14% |
| Business, Management and Accounting | 5 | 9% |
| Social Sciences | 5 | 9% |
| Agricultural and Biological Sciences | 1 | 2% |
| Other | 2 | 3% |
| Unknown | 28 | 48% |