You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
A Systematic DNN Weight Pruning Framework Using Alternating Direction Method of Multipliers
|
|---|---|
| Chapter number | 12 |
| Book title |
Computer Vision – ECCV 2018
|
| Published in |
arXiv, September 2018
|
| DOI | 10.1007/978-3-030-01237-3_12 |
| Book ISBNs |
978-3-03-001236-6, 978-3-03-001237-3
|
| Authors |
Tianyun Zhang, Shaokai Ye, Kaiqi Zhang, Jian Tang, Wujie Wen, Makan Fardad, Yanzhi Wang, Zhang, Tianyun, Ye, Shaokai, Zhang, Kaiqi, Tang, Jian, Wen, Wujie, Fardad, Makan, Wang, Yanzhi |
X Demographics
The data shown below were collected from the profiles of 8 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 | 25% |
| Turkey | 1 | 13% |
| Unknown | 5 | 63% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 88% |
| Scientists | 1 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 208 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 208 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 43 | 21% |
| Student > Master | 27 | 13% |
| Researcher | 18 | 9% |
| Student > Bachelor | 12 | 6% |
| Student > Doctoral Student | 8 | 4% |
| Other | 22 | 11% |
| Unknown | 78 | 38% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 82 | 39% |
| Engineering | 30 | 14% |
| Materials Science | 3 | 1% |
| Economics, Econometrics and Finance | 2 | <1% |
| Mathematics | 2 | <1% |
| Other | 3 | 1% |
| Unknown | 86 | 41% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 26 July 2018.
All research outputs
#7,267,147
of 24,002,307 outputs
Outputs from arXiv
#154,537
of 1,011,770 outputs
Outputs of similar age
#121,845
of 339,604 outputs
Outputs of similar age from arXiv
#4,346
of 24,369 outputs
Altmetric has tracked 24,002,307 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 1,011,770 research outputs from this source. They receive a mean Attention Score of 4.0. This one has done well, scoring higher than 84% 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 339,604 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 63% of its contemporaries.
We're also able to compare this research output to 24,369 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.