↓ Skip to main content

Attention-based 3D convolutional recurrent neural network model for multimodal emotion recognition

Overview of attention for article published in Frontiers in Neuroscience, January 2024
Altmetric Badge

Mentioned by

twitter
2 X users

Readers on

mendeley
2 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Attention-based 3D convolutional recurrent neural network model for multimodal emotion recognition
Published in
Frontiers in Neuroscience, January 2024
DOI 10.3389/fnins.2023.1330077
Pubmed ID
Authors

Yiming Du, Penghai Li, Longlong Cheng, Xuanwei Zhang, Mingji Li, Fengzhou Li

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 50%
Professor 1 50%
Readers by discipline Count As %
Unspecified 1 50%
Computer Science 1 50%
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 03 February 2024.
All research outputs
#20,686,897
of 25,411,814 outputs
Outputs from Frontiers in Neuroscience
#9,469
of 11,552 outputs
Outputs of similar age
#229,967
of 332,196 outputs
Outputs of similar age from Frontiers in Neuroscience
#160
of 225 outputs
Altmetric has tracked 25,411,814 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,552 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one is in the 12th percentile – i.e., 12% 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 332,196 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 225 others from the same source and published within six weeks on either side of this one. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.