Improved facial emotion recognition model based on a novel deep convolutional structure
Reham A Elsheikh, M A Mohamed, Ahmed Mohamed Abou-Taleb, Mohamed Maher Ata · 2024
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Description
Reham Elsheikh and three co-authors build, in 2024 work, a face-reading model that spots eight feelings with high scores. Reading feelings from faces is hard: light, angle, blocked views, and culture all blur the signs. Their twist is a step that fights the blur caused when image layers shrink the picture.
The model and rival tools were tried on three face sets, from posed lab photos to hard real-world shots. Their model topped each set, nearing full marks on the lab sets and scoring well on the hard set, all in short training times. The team credits the anti-blur step for the gain. Such tools could aid fields from care to teaching, they note, if used with care.
Catalog record
| CREATOR | Reham A Elsheikh, M A Mohamed, Ahmed Mohamed Abou-Taleb, Mohamed Maher Ata |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 77 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |