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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Dataset Augmentation with Synthetic Images Improves Semantic Segmentation
|
|---|---|
| Chapter number | 31 |
| Book title |
Computer Vision, Pattern Recognition, Image Processing, and Graphics
|
| Published in |
arXiv, April 2018
|
| DOI | 10.1007/978-981-13-0020-2_31 |
| Book ISBNs |
978-9-81-130019-6, 978-9-81-130020-2
|
| Authors |
Param Rajpura, Manik Goyal, Ravi Hegde, Hristo Bojinov, Goyal, Manik, Rajpura, Param, Bojinov, Hristo, Hegde, Ravi |
X Demographics
The data shown below were collected from the profiles of 9 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 | 2 | 22% |
| Netherlands | 1 | 11% |
| Germany | 1 | 11% |
| India | 1 | 11% |
| Unknown | 4 | 44% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 4 | 44% |
| Members of the public | 4 | 44% |
| Practitioners (doctors, other healthcare professionals) | 1 | 11% |
Mendeley readers
The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 60 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 20% |
| Student > Master | 12 | 20% |
| Researcher | 8 | 13% |
| Student > Bachelor | 6 | 10% |
| Student > Doctoral Student | 5 | 8% |
| Other | 9 | 15% |
| Unknown | 8 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 30 | 50% |
| Engineering | 11 | 18% |
| Unspecified | 2 | 3% |
| Agricultural and Biological Sciences | 1 | 2% |
| Biochemistry, Genetics and Molecular Biology | 1 | 2% |
| Other | 5 | 8% |
| Unknown | 10 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 February 2020.
All research outputs
#4,817,041
of 24,049,457 outputs
Outputs from arXiv
#109,021
of 1,017,649 outputs
Outputs of similar age
#88,991
of 330,327 outputs
Outputs of similar age from arXiv
#2,394
of 23,601 outputs
Altmetric has tracked 24,049,457 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,017,649 research outputs from this source. They receive a mean Attention Score of 4.0. This one has done well, scoring higher than 89% 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 330,327 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 72% of its contemporaries.
We're also able to compare this research output to 23,601 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.