Title |
Real time detection system for rail surface defects based on machine vision
|
---|---|
Published in |
EURASIP Journal on Image and Video Processing, January 2018
|
DOI | 10.1186/s13640-017-0241-y |
Authors |
Yongzhi Min, Benyu Xiao, Jianwu Dang, Biao Yue, Tiandong Cheng |
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 % |
---|---|---|
India | 1 | 50% |
United Kingdom | 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 106 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 106 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Bachelor | 15 | 14% |
Student > Master | 13 | 12% |
Lecturer | 7 | 7% |
Researcher | 6 | 6% |
Student > Doctoral Student | 5 | 5% |
Other | 12 | 11% |
Unknown | 48 | 45% |
Readers by discipline | Count | As % |
---|---|---|
Engineering | 32 | 30% |
Computer Science | 13 | 12% |
Economics, Econometrics and Finance | 3 | 3% |
Mathematics | 1 | <1% |
Chemical Engineering | 1 | <1% |
Other | 2 | 2% |
Unknown | 54 | 51% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 29 January 2022.
All research outputs
#7,050,597
of 25,382,440 outputs
Outputs from EURASIP Journal on Image and Video Processing
#38
of 233 outputs
Outputs of similar age
#132,234
of 450,898 outputs
Outputs of similar age from EURASIP Journal on Image and Video Processing
#4
of 16 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 233 research outputs from this source. They receive a mean Attention Score of 2.9. This one has done well, scoring higher than 83% 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 450,898 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 70% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.