| Title |
Effective Crowd Anomaly Detection Through Spatio-temporal Texture Analysis
|
|---|---|
| Published in |
Machine Intelligence Research, September 2018
|
| DOI | 10.1007/s11633-018-1141-z |
| Authors |
Yu Hao, Zhi-Jie Xu, Ying Liu, Jing Wang, Jiu-Lun Fan |
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 % |
|---|---|---|
| United Kingdom | 1 | 50% |
| China | 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 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 43 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 14% |
| Student > Master | 6 | 14% |
| Student > Bachelor | 4 | 9% |
| Lecturer | 2 | 5% |
| Researcher | 2 | 5% |
| Other | 5 | 12% |
| Unknown | 18 | 42% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 17 | 40% |
| Engineering | 2 | 5% |
| Agricultural and Biological Sciences | 1 | 2% |
| Unspecified | 1 | 2% |
| Chemistry | 1 | 2% |
| Other | 1 | 2% |
| Unknown | 20 | 47% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 16 July 2020.
All research outputs
#19,954,338
of 25,385,509 outputs
Outputs from Machine Intelligence Research
#186
of 444 outputs
Outputs of similar age
#257,266
of 351,592 outputs
Outputs of similar age from Machine Intelligence Research
#4
of 19 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 444 research outputs from this source. They receive a mean Attention Score of 2.5. This one is in the 48th percentile – i.e., 48% of its peers scored the same or lower than it.
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 351,592 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.