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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Estimating Depth from RGB and Sparse Sensing
|
|---|---|
| Chapter number | 11 |
| Book title |
Computer Vision – ECCV 2018
|
| Published in |
arXiv, September 2018
|
| DOI | 10.1007/978-3-030-01225-0_11 |
| Book ISBNs |
978-3-03-001224-3, 978-3-03-001225-0
|
| Authors |
Zhao Chen, Vijay Badrinarayanan, Gilad Drozdov, Andrew Rabinovich, Chen, Zhao, Badrinarayanan, Vijay, Drozdov, Gilad, Rabinovich, Andrew |
X Demographics
The data shown below were collected from the profiles of 44 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 | 10 | 23% |
| China | 2 | 5% |
| Australia | 2 | 5% |
| Indonesia | 1 | 2% |
| Mexico | 1 | 2% |
| Korea, Republic of | 1 | 2% |
| India | 1 | 2% |
| Japan | 1 | 2% |
| Sri Lanka | 1 | 2% |
| Other | 4 | 9% |
| Unknown | 20 | 45% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 36 | 82% |
| Scientists | 8 | 18% |
Mendeley readers
The data shown below were compiled from readership statistics for 226 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 226 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 47 | 21% |
| Researcher | 33 | 15% |
| Student > Master | 27 | 12% |
| Student > Bachelor | 15 | 7% |
| Student > Doctoral Student | 9 | 4% |
| Other | 16 | 7% |
| Unknown | 79 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 103 | 46% |
| Engineering | 29 | 13% |
| Physics and Astronomy | 5 | 2% |
| Biochemistry, Genetics and Molecular Biology | 1 | <1% |
| Agricultural and Biological Sciences | 1 | <1% |
| Other | 2 | <1% |
| Unknown | 85 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 29. 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 05 January 2023.
All research outputs
#1,309,720
of 24,798,538 outputs
Outputs from arXiv
#19,698
of 1,006,223 outputs
Outputs of similar age
#27,821
of 341,436 outputs
Outputs of similar age from arXiv
#419
of 21,849 outputs
Altmetric has tracked 24,798,538 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 1,006,223 research outputs from this source. They receive a mean Attention Score of 4.1. 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 341,436 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 91% of its contemporaries.
We're also able to compare this research output to 21,849 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 98% of its contemporaries.