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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Calib-Net: Calibrating the Low-Cost IMU via Deep Convolutional Neural Network
|
|---|---|
| Published in |
Frontiers in Robotics and AI, January 2022
|
| DOI | 10.3389/frobt.2021.772583 |
| Pubmed ID | |
| Authors |
Ruihao Li, Chunlian Fu, Wei Yi, Xiaodong Yi |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 13% |
| Mexico | 1 | 13% |
| Germany | 1 | 13% |
| Unknown | 5 | 63% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 8 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 35 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 14% |
| Student > Master | 4 | 11% |
| Student > Doctoral Student | 2 | 6% |
| Other | 1 | 3% |
| Researcher | 1 | 3% |
| Other | 0 | 0% |
| Unknown | 22 | 63% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 6 | 17% |
| Computer Science | 4 | 11% |
| Chemical Engineering | 1 | 3% |
| Neuroscience | 1 | 3% |
| Social Sciences | 1 | 3% |
| Other | 0 | 0% |
| Unknown | 22 | 63% |
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 04 January 2022.
All research outputs
#7,404,706
of 22,813,792 outputs
Outputs from Frontiers in Robotics and AI
#513
of 1,491 outputs
Outputs of similar age
#166,150
of 499,141 outputs
Outputs of similar age from Frontiers in Robotics and AI
#38
of 101 outputs
Altmetric has tracked 22,813,792 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 1,491 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.8. This one has gotten more attention than average, scoring higher than 64% 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 499,141 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 66% of its contemporaries.
We're also able to compare this research output to 101 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.