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Imbalanced Deep Learning by Minority Class Incremental Rectification

Overview of attention for article published in IEEE Transactions on Software Engineering, May 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (84th percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

Mentioned by

twitter
1 X user
patent
9 patents
q&a
1 Q&A thread

Readers on

mendeley
370 Mendeley
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Article details
Title
Imbalanced Deep Learning by Minority Class Incremental Rectification
Published in
IEEE Transactions on Software Engineering, May 2018
DOI 10.1109/tpami.2018.2832629
Pubmed ID
Authors

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Timeline Attention over time Attention Score history
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Activity
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X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 370 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 370 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 83 22%
Student > Master 47 13%
Researcher 38 10%
Student > Bachelor 18 5%
Student > Doctoral Student 16 4%
Other 44 12%
Unknown 124 34%
Readers by discipline
Readers by discipline Count As %
Computer Science 148 40%
Engineering 35 9%
Medicine and Dentistry 6 2%
Business, Management and Accounting 5 1%
Agricultural and Biological Sciences 5 1%
Other 30 8%
Unknown 141 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 10 June 2025.
All research outputs
#3,779,846
of 34,376,207 outputs
Outputs from IEEE Transactions on Software Engineering
#626
of 7,914 outputs
Outputs of similar age
#57,641
of 370,428 outputs
Outputs of similar age from IEEE Transactions on Software Engineering
#9
of 68 outputs
Altmetric has tracked 34,376,207 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,914 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.0. This one has done well, scoring higher than 89% 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 370,428 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 84% of its contemporaries.
We're also able to compare this research output to 68 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.