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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Automatic Diagnosis of Rice Diseases Using Deep Learning
|
|---|---|
| Published in |
Frontiers in Plant Science, August 2021
|
| DOI | 10.3389/fpls.2021.701038 |
| Pubmed ID | |
| Authors |
Ruoling Deng, Ming Tao, Hang Xing, Xiuli Yang, Chuang Liu, Kaifeng Liao, Long Qi |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 1 | 14% |
| Pakistan | 1 | 14% |
| United States | 1 | 14% |
| Unknown | 4 | 57% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 86% |
| Scientists | 1 | 14% |
Mendeley readers
The data shown below were compiled from readership statistics for 132 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 132 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 6% |
| Student > Master | 8 | 6% |
| Lecturer | 7 | 5% |
| Student > Ph. D. Student | 6 | 5% |
| Student > Bachelor | 4 | 3% |
| Other | 15 | 11% |
| Unknown | 84 | 64% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 21 | 16% |
| Engineering | 9 | 7% |
| Agricultural and Biological Sciences | 9 | 7% |
| Unspecified | 2 | 2% |
| Mathematics | 1 | <1% |
| Other | 4 | 3% |
| Unknown | 86 | 65% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 03 March 2022.
All research outputs
#6,453,639
of 23,577,761 outputs
Outputs from Frontiers in Plant Science
#3,554
of 21,632 outputs
Outputs of similar age
#128,333
of 433,667 outputs
Outputs of similar age from Frontiers in Plant Science
#140
of 828 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 21,632 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done well, scoring higher than 83% 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 433,667 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 70% of its contemporaries.
We're also able to compare this research output to 828 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.