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Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images

Overview of attention for article published in arXiv, December 2014
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#16 of 491,170)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
11 news outlets
blogs
5 blogs
twitter
1191 tweeters
weibo
5 weibo users
facebook
33 Facebook pages
googleplus
66 Google+ users
reddit
5 Redditors
q&a
2 Q&A threads

Readers on

mendeley
1603 Mendeley
citeulike
1 CiteULike
Title
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images
Published in
arXiv, December 2014
Authors

Anh Nguyen, Jason Yosinski, Jeff Clune

Twitter Demographics

The data shown below were collected from the profiles of 1,191 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 1,603 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 36 2%
United Kingdom 22 1%
Germany 18 1%
China 12 <1%
Italy 10 <1%
Japan 8 <1%
Spain 7 <1%
Australia 5 <1%
Turkey 4 <1%
Other 34 2%
Unknown 1447 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 502 31%
Student > Master 367 23%
Researcher 246 15%
Student > Bachelor 190 12%
Other 81 5%
Other 217 14%
Readers by discipline Count As %
Computer Science 1013 63%
Engineering 242 15%
Physics and Astronomy 66 4%
Agricultural and Biological Sciences 58 4%
Unspecified 39 2%
Other 185 12%

Attention Score in Context

This research output has an Altmetric Attention Score of 1079. 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 04 November 2017.
All research outputs
#1,691
of 8,636,379 outputs
Outputs from arXiv
#16
of 491,170 outputs
Outputs of similar age
#55
of 242,905 outputs
Outputs of similar age from arXiv
#2
of 22,161 outputs
Altmetric has tracked 8,636,379 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 491,170 research outputs from this source. They receive a mean Attention Score of 2.8. This one has done particularly well, scoring higher than 99% 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 242,905 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 22,161 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.