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Individual Tree-Crown Detection and Species Identification in Heterogeneous Forests Using Aerial RGB Imagery and Deep Learning

Overview of attention for article published in Remote Sensing, March 2023
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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 (#19 of 13,713)
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

twitter
253 X users
peer_reviews
1 peer review site

Citations

dimensions_citation
13 Dimensions

Readers on

mendeley
89 Mendeley
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Title
Individual Tree-Crown Detection and Species Identification in Heterogeneous Forests Using Aerial RGB Imagery and Deep Learning
Published in
Remote Sensing, March 2023
DOI 10.3390/rs15051463
Authors

Mirela Beloiu, Lucca Heinzmann, Nataliia Rehush, Arthur Gessler, Verena C. Griess

X Demographics

X Demographics

The data shown below were collected from the profiles of 253 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 89 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 89 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 12%
Student > Bachelor 7 8%
Student > Master 7 8%
Student > Doctoral Student 4 4%
Researcher 4 4%
Other 5 6%
Unknown 51 57%
Readers by discipline Count As %
Environmental Science 15 17%
Earth and Planetary Sciences 6 7%
Agricultural and Biological Sciences 5 6%
Engineering 3 3%
Medicine and Dentistry 2 2%
Other 5 6%
Unknown 53 60%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 174. 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 19 March 2024.
All research outputs
#237,551
of 25,848,323 outputs
Outputs from Remote Sensing
#19
of 13,713 outputs
Outputs of similar age
#5,957
of 427,706 outputs
Outputs of similar age from Remote Sensing
#1
of 474 outputs
Altmetric has tracked 25,848,323 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 13,713 research outputs from this source. They receive a mean Attention Score of 4.5. 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 427,706 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 98% of its contemporaries.
We're also able to compare this research output to 474 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.