| Title |
Utilization of computer vision and multispectral imaging techniques for classification of cowpea (Vigna unguiculata) seeds
|
|---|---|
| Published in |
Plant Methods, March 2019
|
| DOI | 10.1186/s13007-019-0411-2 |
| Pubmed ID | |
| Authors |
Gamal ElMasry, Nasser Mandour, Marie-Hélène Wagner, Didier Demilly, Jerome Verdier, Etienne Belin, David Rousseau |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 1 | 50% |
| United Kingdom | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Science communicators (journalists, bloggers, editors) | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 83 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 83 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 18 | 22% |
| Student > Master | 12 | 14% |
| Researcher | 8 | 10% |
| Student > Doctoral Student | 5 | 6% |
| Lecturer | 4 | 5% |
| Other | 11 | 13% |
| Unknown | 25 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 26 | 31% |
| Computer Science | 9 | 11% |
| Engineering | 7 | 8% |
| Biochemistry, Genetics and Molecular Biology | 4 | 5% |
| Business, Management and Accounting | 1 | 1% |
| Other | 6 | 7% |
| Unknown | 30 | 36% |
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 14 March 2019.
All research outputs
#14,907,277
of 23,133,982 outputs
Outputs from Plant Methods
#766
of 1,095 outputs
Outputs of similar age
#205,995
of 351,336 outputs
Outputs of similar age from Plant Methods
#23
of 37 outputs
Altmetric has tracked 23,133,982 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,095 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one is in the 28th percentile – i.e., 28% of its peers scored the same or lower than it.
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 351,336 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 37 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.