Scale Space and Variational Methods in Computer Vision
Springer International Publishing
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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
CLIP: Cheap Lipschitz Training of Neural Networks
|
|---|---|
| Book title |
Scale Space and Variational Methods in Computer Vision
|
| Published in |
arXiv, April 2021
|
| DOI | 10.1007/978-3-030-75549-2_25 |
| Book ISBNs |
978-3-03-075548-5, 978-3-03-075549-2
|
| Authors |
Leon Bungert, René Raab, Tim Roith, Leo Schwinn, Daniel Tenbrinck, Bungert, Leon, Raab, René, Roith, Tim, Schwinn, Leo, Tenbrinck, Daniel |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 4 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 16 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Doctoral Student | 2 | 13% |
| Student > Bachelor | 2 | 13% |
| Researcher | 2 | 13% |
| Student > Master | 2 | 13% |
| Unspecified | 1 | 6% |
| Other | 2 | 13% |
| Unknown | 5 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 3 | 19% |
| Engineering | 3 | 19% |
| Mathematics | 2 | 13% |
| Physics and Astronomy | 1 | 6% |
| Unspecified | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 6 | 38% |
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 02 November 2022.
All research outputs
#14,968,843
of 23,025,074 outputs
Outputs from arXiv
#324,778
of 945,278 outputs
Outputs of similar age
#242,303
of 435,261 outputs
Outputs of similar age from arXiv
#11,573
of 34,825 outputs
Altmetric has tracked 23,025,074 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 945,278 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 435,261 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 34,825 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.