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Attention Score in Context
| Title |
Deep-Learning-Based Sequence Causal Long-Term Recurrent Convolutional Network for Data Fusion Using Video Data
|
|---|---|
| Published in |
Electronics, February 2023
|
| DOI | 10.3390/electronics12051115 |
| Authors |
DaeHyeon Jeon, Min-Suk Kim |
Attention Score in Context
This research output has an Altmetric Attention Score of 501. 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 30 March 2023.
All research outputs
#44,182
of 23,504,445 outputs
Outputs from Electronics
#1
of 2,796 outputs
Outputs of similar age
#1,047
of 378,872 outputs
Outputs of similar age from Electronics
#1
of 107 outputs
Altmetric has tracked 23,504,445 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 2,796 research outputs from this source. They receive a mean Attention Score of 3.3. 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 378,872 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 107 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.