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Comparison of Early Stopping Criteria for Neural-Network-Based Subpixel Classification

Overview of attention for article published in IEEE Geoscience and Remote Sensing Letters, July 2010
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (69th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

patent
2 patents

Readers on

mendeley
29 Mendeley
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Article details
Title
Comparison of Early Stopping Criteria for Neural-Network-Based Subpixel Classification
Published in
IEEE Geoscience and Remote Sensing Letters, July 2010
DOI 10.1109/lgrs.2010.2052782
Authors

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Timeline Attention over time Attention Score history
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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 29 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 10 34%
Student > Master 5 17%
Student > Doctoral Student 2 7%
Student > Bachelor 2 7%
Researcher 2 7%
Other 3 10%
Unknown 5 17%
Readers by discipline
Readers by discipline Count As %
Computer Science 6 21%
Engineering 6 21%
Environmental Science 3 10%
Earth and Planetary Sciences 3 10%
Physics and Astronomy 1 3%
Other 1 3%
Unknown 9 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 23 May 2023.
All research outputs
#6,762,183
of 31,482,640 outputs
Outputs from IEEE Geoscience and Remote Sensing Letters
#113
of 2,095 outputs
Outputs of similar age
#28,403
of 133,356 outputs
Outputs of similar age from IEEE Geoscience and Remote Sensing Letters
#1
of 16 outputs
Altmetric has tracked 31,482,640 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 2,095 research outputs from this source. They receive a mean Attention Score of 3.5. This one has done well, scoring higher than 88% 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 133,356 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 69% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.