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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Deep Plant Phenomics: A Deep Learning Platform for Complex Plant Phenotyping Tasks
|
|---|---|
| Published in |
Frontiers in Plant Science, July 2017
|
| DOI | 10.3389/fpls.2017.01190 |
| Pubmed ID | |
| Authors |
Jordan R. Ubbens, Ian Stavness |
| Abstract |
Plant phenomics has received increasing interest in recent years in an attempt to bridge the genotype-to-phenotype knowledge gap. There is a need for expanded high-throughput phenotyping capabilities to keep up with an increasing amount of data from high-dimensional imaging sensors and the desire to measure more complex phenotypic traits (Knecht et al., 2016). In this paper, we introduce an open-source deep learning tool called Deep Plant Phenomics. This tool provides pre-trained neural networks for several common plant phenotyping tasks, as well as an easy platform that can be used by plant scientists to train models for their own phenotyping applications. We report performance results on three plant phenotyping benchmarks from the literature, including state of the art performance on leaf counting, as well as the first published results for the mutant classification and age regression tasks for Arabidopsis thaliana. |
X Demographics
The data shown below were collected from the profiles of 31 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 | 11 | 35% |
| Canada | 4 | 13% |
| Netherlands | 2 | 6% |
| India | 2 | 6% |
| Germany | 2 | 6% |
| Switzerland | 1 | 3% |
| Austria | 1 | 3% |
| Belgium | 1 | 3% |
| Taiwan | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 5 | 16% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 20 | 65% |
| Scientists | 11 | 35% |
Mendeley readers
The data shown below were compiled from readership statistics for 435 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 435 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 80 | 18% |
| Researcher | 78 | 18% |
| Student > Master | 65 | 15% |
| Student > Bachelor | 35 | 8% |
| Student > Postgraduate | 17 | 4% |
| Other | 63 | 14% |
| Unknown | 97 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 140 | 32% |
| Computer Science | 60 | 14% |
| Engineering | 49 | 11% |
| Biochemistry, Genetics and Molecular Biology | 23 | 5% |
| Environmental Science | 7 | 2% |
| Other | 29 | 7% |
| Unknown | 127 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 25. 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 27 July 2019.
All research outputs
#1,489,940
of 24,970,080 outputs
Outputs from Frontiers in Plant Science
#469
of 23,919 outputs
Outputs of similar age
#28,846
of 318,429 outputs
Outputs of similar age from Frontiers in Plant Science
#14
of 540 outputs
Altmetric has tracked 24,970,080 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 23,919 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done particularly well, scoring higher than 98% 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 318,429 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 540 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.