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Attention Score in Context
| Title |
DOA Estimation Based on Convolutional Autoencoder in the Presence of Array Imperfections
|
|---|---|
| Published in |
Electronics, February 2023
|
| DOI | 10.3390/electronics12030771 |
| Authors |
Dah-Chung Chang, Yan-Ting Liu |
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 16 February 2023.
All research outputs
#3,902,163
of 23,372,207 outputs
Outputs from Electronics
#144
of 2,754 outputs
Outputs of similar age
#62,437
of 393,252 outputs
Outputs of similar age from Electronics
#12
of 116 outputs
Altmetric has tracked 23,372,207 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 2,754 research outputs from this source. They receive a mean Attention Score of 3.1. This one has done particularly well, scoring higher than 93% 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 393,252 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 83% of its contemporaries.
We're also able to compare this research output to 116 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.