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Robust and accurate feature selection for humanoid push recovery and classification: deep learning approach

Overview of attention for article published in Neural Computing and Applications, November 2015
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  • Average Attention Score compared to outputs of the same age
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
2 X users

Citations

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119 Dimensions

Readers on

mendeley
63 Mendeley
Title
Robust and accurate feature selection for humanoid push recovery and classification: deep learning approach
Published in
Neural Computing and Applications, November 2015
DOI 10.1007/s00521-015-2089-3
Authors

Vijay Bhaskar Semwal, Kaushik Mondal, G. C. Nandi

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 63 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 11 17%
Student > Ph. D. Student 8 13%
Student > Bachelor 5 8%
Student > Doctoral Student 5 8%
Researcher 4 6%
Other 14 22%
Unknown 16 25%
Readers by discipline Count As %
Engineering 20 32%
Computer Science 13 21%
Biochemistry, Genetics and Molecular Biology 1 2%
Nursing and Health Professions 1 2%
Business, Management and Accounting 1 2%
Other 5 8%
Unknown 22 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 06 April 2017.
All research outputs
#14,398,884
of 23,839,820 outputs
Outputs from Neural Computing and Applications
#358
of 2,407 outputs
Outputs of similar age
#197,376
of 391,428 outputs
Outputs of similar age from Neural Computing and Applications
#6
of 10 outputs
Altmetric has tracked 23,839,820 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,407 research outputs from this source. They receive a mean Attention Score of 1.3. This one has done well, scoring higher than 84% 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 391,428 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.