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X Demographics
Attention Score in Context
| Title |
CLIB: Contrastive learning of ignoring background for underwater fish image classification
|
|---|---|
| Published in |
Frontiers in Neurorobotics, July 2024
|
| DOI | 10.3389/fnbot.2024.1423848 |
| Pubmed ID | |
| Authors |
Qiankun Yan, Xiujuan Du, Chong Li, Xiaojing Tian |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
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 02 August 2024.
All research outputs
#23,721,795
of 26,404,318 outputs
Outputs from Frontiers in Neurorobotics
#832
of 1,065 outputs
Outputs of similar age
#108,389
of 139,846 outputs
Outputs of similar age from Frontiers in Neurorobotics
#1
of 4 outputs
Altmetric has tracked 26,404,318 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 1,065 research outputs from this source. They receive a mean Attention Score of 4.2. 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 139,846 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 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them