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X Demographics
Mendeley readers
Attention Score in Context
Title |
Exploiting Temporal Information for DCNN-Based Fine-Grained Object Classification
|
---|---|
Published in |
arXiv, November 2016
|
DOI | 10.1109/dicta.2016.7797039 |
Authors |
ZongYuan Ge, Chris McCool, Conrad Sanderson, Peng Wang, Lingqiao Liu, Ian Reid, Peter Corke |
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 % |
---|---|---|
United States | 1 | 25% |
Unknown | 3 | 75% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 34 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 11 | 32% |
Researcher | 4 | 12% |
Other | 3 | 9% |
Student > Postgraduate | 3 | 9% |
Student > Master | 3 | 9% |
Other | 5 | 15% |
Unknown | 5 | 15% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 17 | 50% |
Engineering | 6 | 18% |
Agricultural and Biological Sciences | 2 | 6% |
Neuroscience | 1 | 3% |
Physics and Astronomy | 1 | 3% |
Other | 0 | 0% |
Unknown | 7 | 21% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 11 November 2016.
All research outputs
#7,486,175
of 22,881,964 outputs
Outputs from arXiv
#168,747
of 939,591 outputs
Outputs of similar age
#113,678
of 311,719 outputs
Outputs of similar age from arXiv
#2,941
of 16,598 outputs
Altmetric has tracked 22,881,964 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 939,591 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done well, scoring higher than 80% 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 311,719 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 51% of its contemporaries.
We're also able to compare this research output to 16,598 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.