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FPGA-Based High-Performance Collision Detection: An Enabling Technique for Image-Guided Robotic Surgery

Overview of attention for article published in Frontiers in Robotics and AI, August 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • Good Attention Score compared to outputs of the same age and source (73rd percentile)

Mentioned by

twitter
6 X users
patent
1 patent

Readers on

mendeley
24 Mendeley
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Title
FPGA-Based High-Performance Collision Detection: An Enabling Technique for Image-Guided Robotic Surgery
Published in
Frontiers in Robotics and AI, August 2016
DOI 10.3389/frobt.2016.00051
Authors

Zhaorui Zhang, Yao Xin, Benben Liu, Will X. Y. Li, Kit-Hang Lee, Chun-Fai Ng, Danail Stoyanov, Ray C. C. Cheung, Ka-Wai Kwok

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 3 13%
Student > Ph. D. Student 3 13%
Student > Master 2 8%
Student > Doctoral Student 1 4%
Professor 1 4%
Other 3 13%
Unknown 11 46%
Readers by discipline Count As %
Engineering 8 33%
Computer Science 2 8%
Medicine and Dentistry 2 8%
Psychology 1 4%
Unknown 11 46%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 27 July 2022.
All research outputs
#4,095,305
of 22,962,258 outputs
Outputs from Frontiers in Robotics and AI
#264
of 1,505 outputs
Outputs of similar age
#69,623
of 337,960 outputs
Outputs of similar age from Frontiers in Robotics and AI
#5
of 19 outputs
Altmetric has tracked 22,962,258 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,505 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.7. This one has done well, scoring higher than 82% 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 337,960 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 79% of its contemporaries.
We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.