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Mendeley readers
Attention Score in Context
| Title |
Facial expression (mood) recognition from facial images using committee neural networks
|
|---|---|
| Published in |
BioMedical Engineering OnLine, August 2009
|
| DOI | 10.1186/1475-925x-8-16 |
| Pubmed ID | |
| Authors |
Saket S Kulkarni, Narender P Reddy, SI Hariharan |
| Abstract |
Facial expressions are important in facilitating human communication and interactions. Also, they are used as an important tool in behavioural studies and in medical rehabilitation. Facial image based mood detection techniques may provide a fast and practical approach for non-invasive mood detection. The purpose of the present study was to develop an intelligent system for facial image based expression classification using committee neural networks. |
Mendeley readers
The data shown below were compiled from readership statistics for 107 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 2% |
| Mexico | 1 | <1% |
| United States | 1 | <1% |
| India | 1 | <1% |
| Unknown | 102 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 22 | 21% |
| Student > Bachelor | 16 | 15% |
| Student > Ph. D. Student | 11 | 10% |
| Researcher | 10 | 9% |
| Student > Doctoral Student | 9 | 8% |
| Other | 19 | 18% |
| Unknown | 20 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 41 | 38% |
| Engineering | 18 | 17% |
| Agricultural and Biological Sciences | 4 | 4% |
| Medicine and Dentistry | 4 | 4% |
| Psychology | 3 | 3% |
| Other | 14 | 13% |
| Unknown | 23 | 21% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. 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 13 July 2021.
All research outputs
#2,435,662
of 22,705,019 outputs
Outputs from BioMedical Engineering OnLine
#52
of 821 outputs
Outputs of similar age
#8,911
of 110,841 outputs
Outputs of similar age from BioMedical Engineering OnLine
#1
of 3 outputs
Altmetric has tracked 22,705,019 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 821 research outputs from this source. They receive a mean Attention Score of 4.6. 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 110,841 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 91% of its contemporaries.
We're also able to compare this research output to 3 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