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Mendeley readers
Attention Score in Context
| Title |
Surface feature based classification of plant organs from 3D laserscanned point clouds for plant phenotyping
|
|---|---|
| Published in |
BMC Bioinformatics, July 2013
|
| DOI | 10.1186/1471-2105-14-238 |
| Pubmed ID | |
| Authors |
Stefan Paulus, Jan Dupuis, Anne-Katrin Mahlein, Heiner Kuhlmann |
| Abstract |
Laserscanning recently has become a powerful and common method for plant parameterization and plant growth observation on nearly every scale range. However, 3D measurements with high accuracy, spatial resolution and speed result in a multitude of points that require processing and analysis. The primary objective of this research has been to establish a reliable and fast technique for high throughput phenotyping using differentiation, segmentation and classification of single plants by a fully automated system. In this report, we introduce a technique for automated classification of point clouds of plants and present the applicability for plant parameterization. |
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 % |
|---|---|---|
| United States | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 158 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 2 | 1% |
| United States | 2 | 1% |
| Australia | 1 | <1% |
| France | 1 | <1% |
| Spain | 1 | <1% |
| Brazil | 1 | <1% |
| Unknown | 150 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 37 | 23% |
| Researcher | 31 | 20% |
| Student > Master | 23 | 15% |
| Student > Doctoral Student | 10 | 6% |
| Student > Bachelor | 10 | 6% |
| Other | 19 | 12% |
| Unknown | 28 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 55 | 35% |
| Computer Science | 28 | 18% |
| Engineering | 20 | 13% |
| Environmental Science | 8 | 5% |
| Earth and Planetary Sciences | 5 | 3% |
| Other | 11 | 7% |
| Unknown | 31 | 20% |
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 16 June 2015.
All research outputs
#14,931,785
of 23,881,329 outputs
Outputs from BMC Bioinformatics
#4,825
of 7,454 outputs
Outputs of similar age
#114,276
of 201,020 outputs
Outputs of similar age from BMC Bioinformatics
#53
of 82 outputs
Altmetric has tracked 23,881,329 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 7,454 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 31st percentile – i.e., 31% 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 201,020 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 82 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.