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Cross-modal subspace learning for fine-grained sketch-based image retrieval

Overview of attention for article published in Neurocomputing, February 2018
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Mentioned by

patent
1 patent

Readers on

mendeley
46 Mendeley
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Article details
Title
Cross-modal subspace learning for fine-grained sketch-based image retrieval
Published in
Neurocomputing, February 2018
DOI 10.1016/j.neucom.2017.05.099
Authors

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 46 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 11 24%
Student > Master 8 17%
Student > Doctoral Student 4 9%
Lecturer 3 7%
Student > Bachelor 2 4%
Other 6 13%
Unknown 12 26%
Readers by discipline
Readers by discipline Count As %
Computer Science 21 46%
Engineering 6 13%
Biochemistry, Genetics and Molecular Biology 1 2%
Mathematics 1 2%
Design 1 2%
Other 0 0%
Unknown 16 35%
Attention Score in Context

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 17 January 2023.
All research outputs
#9,515,768
of 27,788,586 outputs
Outputs from Neurocomputing
#621
of 3,290 outputs
Outputs of similar age
#165,826
of 456,232 outputs
Outputs of similar age from Neurocomputing
#21
of 77 outputs
Altmetric has tracked 27,788,586 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,290 research outputs from this source. They receive a mean Attention Score of 2.8. This one has gotten more attention than average, scoring higher than 57% 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 456,232 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 50% of its contemporaries.
We're also able to compare this research output to 77 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.