This journal explores a lightweight deep-learning approach for recognizing human emotions from facial images.
Using the MobileNetV2 architecture, it delivers high accuracy while maintaining low computational requirements.
The model processes facial features efficiently, making it suitable for real-time and mobile applications.
Its resource-optimized design ensures fast performance without compromising recognition quality.
For more information, click on the link below.
National Academy Science Letters (SCIE)
2025
https://link.springer.com/article/10.1007/s40009-025-01671-w