| Title |
Automated Classification of Airborne Pollen using Neural Networks
|
|---|---|
| Published in |
Conference proceedings Annual International Conference of the IEEE Engineering in Medicine and Biology Society, July 2019
|
| DOI | 10.1109/embc.2019.8856910 |
| Pubmed ID | |
| Authors |
Julian Schiele, Fabian Rabe, Maximilian Schmitt, Manuel Glaser, Franziska Häring, Jens O. Brunner, Bernhard Bauer, Björn Schuller, Claudia Traidl-Hoffmann, Athanasios Damialis |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Greece | 1 | 17% |
| Ireland | 1 | 17% |
| Germany | 1 | 17% |
| Unknown | 3 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 50% |
| Practitioners (doctors, other healthcare professionals) | 2 | 33% |
| Members of the public | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 25 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 28% |
| Researcher | 4 | 16% |
| Student > Bachelor | 2 | 8% |
| Librarian | 1 | 4% |
| Other | 1 | 4% |
| Other | 3 | 12% |
| Unknown | 7 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 5 | 20% |
| Earth and Planetary Sciences | 3 | 12% |
| Computer Science | 2 | 8% |
| Social Sciences | 2 | 8% |
| Environmental Science | 2 | 8% |
| Other | 3 | 12% |
| Unknown | 8 | 32% |
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 22 January 2020.
All research outputs
#7,029,857
of 25,385,509 outputs
Outputs from Conference proceedings Annual International Conference of the IEEE Engineering in Medicine and Biology Society
#666
of 4,377 outputs
Outputs of similar age
#119,304
of 363,724 outputs
Outputs of similar age from Conference proceedings Annual International Conference of the IEEE Engineering in Medicine and Biology Society
#46
of 311 outputs
Altmetric has tracked 25,385,509 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 4,377 research outputs from this source. They receive a mean Attention Score of 2.7. This one has done well, scoring higher than 84% 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 363,724 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 67% of its contemporaries.
We're also able to compare this research output to 311 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.