Computer Vision – ECCV 2020
Springer International Publishing
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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
CLAWS: Clustering Assisted Weakly Supervised Learning with Normalcy Suppression for Anomalous Event Detection
|
|---|---|
| Book title |
Computer Vision – ECCV 2020
|
| Published in |
arXiv, November 2020
|
| DOI | 10.1007/978-3-030-58542-6_22 |
| Book ISBNs |
978-3-03-058541-9, 978-3-03-058542-6
|
| Authors |
Muhammad Zaigham Zaheer, Arif Mahmood, Marcella Astrid, Seung-Ik Lee, Zaheer, Muhammad Zaigham, Mahmood, Arif, Astrid, Marcella, Lee, Seung-Ik |
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 % |
|---|---|---|
| Japan | 1 | 25% |
| United States | 1 | 25% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 80 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 16 | 20% |
| Student > Ph. D. Student | 12 | 15% |
| Student > Bachelor | 3 | 4% |
| Researcher | 3 | 4% |
| Student > Doctoral Student | 2 | 3% |
| Other | 3 | 4% |
| Unknown | 41 | 51% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 26 | 33% |
| Engineering | 9 | 11% |
| Biochemistry, Genetics and Molecular Biology | 1 | 1% |
| Economics, Econometrics and Finance | 1 | 1% |
| Agricultural and Biological Sciences | 1 | 1% |
| Other | 2 | 3% |
| Unknown | 40 | 50% |
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 05 August 2021.
All research outputs
#14,879,188
of 24,093,053 outputs
Outputs from arXiv
#262,290
of 1,018,817 outputs
Outputs of similar age
#268,036
of 510,563 outputs
Outputs of similar age from arXiv
#8,590
of 34,409 outputs
Altmetric has tracked 24,093,053 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,018,817 research outputs from this source. They receive a mean Attention Score of 4.0. This one has gotten more attention than average, scoring higher than 71% 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 510,563 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 34,409 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 72% of its contemporaries.