Computer Vision – ECCV 2020
Springer International Publishing
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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Online Ensemble Model Compression Using Knowledge Distillation
|
|---|---|
| Book title |
Computer Vision – ECCV 2020
|
| Published in |
arXiv, November 2020
|
| DOI | 10.1007/978-3-030-58529-7_2 |
| Book ISBNs |
978-3-03-058528-0, 978-3-03-058529-7
|
| Authors |
Devesh Walawalkar, Zhiqiang Shen, Marios Savvides, Walawalkar, Devesh, Shen, Zhiqiang, Savvides, Marios |
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 % |
|---|---|---|
| Japan | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 77 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 22 | 29% |
| Student > Master | 13 | 17% |
| Researcher | 4 | 5% |
| Student > Bachelor | 1 | 1% |
| Student > Doctoral Student | 1 | 1% |
| Other | 1 | 1% |
| Unknown | 35 | 45% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 28 | 36% |
| Engineering | 10 | 13% |
| Materials Science | 1 | 1% |
| Economics, Econometrics and Finance | 1 | 1% |
| Unknown | 37 | 48% |
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 17 November 2020.
All research outputs
#15,152,619
of 23,305,591 outputs
Outputs from arXiv
#329,997
of 960,727 outputs
Outputs of similar age
#241,665
of 414,470 outputs
Outputs of similar age from arXiv
#11,781
of 35,139 outputs
Altmetric has tracked 23,305,591 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 960,727 research outputs from this source. They receive a mean Attention Score of 3.9. This one has gotten more attention than average, scoring higher than 60% 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 414,470 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 35,139 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.