Deep convolutional neural network architecture for facial emotion recognition
Dayananda Pruthviraja, Ujjwal Mohan Kumar, Sunil Parameswaran, Vemulapalli Guna Chowdary, Varun Bharadwaj · 2024
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Description
Dayananda Pruthviraja and co-authors design a deep network that reads emotions from facial images. Emotion reading supports human-computer interaction and mental health research. Reliable reading needs fine facial detail plus robust training.
Their convolutional design stacks layers that extract features on their own. Early layers catch subtle details like brow and lip shifts. Later layers build higher patterns tied to each emotion. Tests used a standard benchmark of labeled face images. The model beat traditional methods on accuracy there. Transfer learning helped when labeled data were scarce. Pretrained networks adapted well to narrow emotion tasks. The study supports deep designs for affect-aware software and smart devices.
Catalog record
| CREATOR | Dayananda Pruthviraja, Ujjwal Mohan Kumar, Sunil Parameswaran, Vemulapalli Guna Chowdary, Varun Bharadwaj |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 37 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |