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Automatic landslide identification by Dual Graph Convolutional Network and GoogLeNet model-a case study for Xinjiang province, China

Overview of attention for article published in Frontiers in Earth Science, September 2023
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Title
Automatic landslide identification by Dual Graph Convolutional Network and GoogLeNet model-a case study for Xinjiang province, China
Published in
Frontiers in Earth Science, September 2023
DOI 10.3389/feart.2023.1248340
Authors

Shiwei Ma, Shouding Li, Xintao Bi, Hua Qiao, Zhigang Duan, Yiming Sun, Jingyun Guo, Xiao Li

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Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 22 September 2023.
All research outputs
#21,946,049
of 24,486,486 outputs
Outputs from Frontiers in Earth Science
#3,549
of 5,740 outputs
Outputs of similar age
#127,621
of 157,982 outputs
Outputs of similar age from Frontiers in Earth Science
#61
of 164 outputs
Altmetric has tracked 24,486,486 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,740 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 157,982 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 164 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.