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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Design and Implementation of a Convolutional Neural Network on an Edge Computing Smartphone for Human Activity Recognition
|
|---|---|
| Published in |
IEEE Access, September 2019
|
| DOI | 10.1109/access.2019.2941836 |
| Authors |
Tahmina Zebin, Patricia J. Scully, Niels Peek, Alexander J. Casson, Krikor B. Ozanyan |
X Demographics
The data shown below were collected from the profiles of 3 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 | 33% |
| Ireland | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 67% |
| Members of the public | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 120 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 120 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 17 | 14% |
| Student > Bachelor | 10 | 8% |
| Unspecified | 7 | 6% |
| Professor | 6 | 5% |
| Student > Master | 6 | 5% |
| Other | 17 | 14% |
| Unknown | 57 | 48% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 27 | 23% |
| Engineering | 22 | 18% |
| Unspecified | 7 | 6% |
| Medicine and Dentistry | 3 | 3% |
| Sports and Recreations | 2 | 2% |
| Other | 3 | 3% |
| Unknown | 56 | 47% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 24 February 2022.
All research outputs
#6,303,376
of 25,385,509 outputs
Outputs from IEEE Access
#1,866
of 9,882 outputs
Outputs of similar age
#99,716
of 338,147 outputs
Outputs of similar age from IEEE Access
#126
of 566 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,882 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done well, scoring higher than 81% 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 338,147 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 566 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.