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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Deep learning-based segmentation and classification of leaf images for detection of tomato plant disease
|
|---|---|
| Published in |
Frontiers in Plant Science, October 2022
|
| DOI | 10.3389/fpls.2022.1031748 |
| Pubmed ID | |
| Authors |
Muhammad Shoaib, Tariq Hussain, Babar Shah, Ihsan Ullah, Sayyed Mudassar Shah, Farman Ali, Sang Hyun Park |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 25% |
| Korea, Democratic People's Republic of | 1 | 25% |
| Switzerland | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 127 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 127 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 9 | 7% |
| Unspecified | 8 | 6% |
| Student > Bachelor | 8 | 6% |
| Student > Ph. D. Student | 8 | 6% |
| Researcher | 7 | 6% |
| Other | 14 | 11% |
| Unknown | 73 | 57% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 25 | 20% |
| Engineering | 13 | 10% |
| Unspecified | 8 | 6% |
| Agricultural and Biological Sciences | 3 | 2% |
| Philosophy | 1 | <1% |
| Other | 0 | 0% |
| Unknown | 77 | 61% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 October 2022.
All research outputs
#14,814,921
of 23,801,276 outputs
Outputs from Frontiers in Plant Science
#8,581
of 21,870 outputs
Outputs of similar age
#206,065
of 444,464 outputs
Outputs of similar age from Frontiers in Plant Science
#441
of 1,469 outputs
Altmetric has tracked 23,801,276 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 21,870 research outputs from this source. They receive a mean Attention Score of 3.9. This one has gotten more attention than average, scoring higher than 59% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 444,464 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.
We're also able to compare this research output to 1,469 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.