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EmotionNet Nano: An Efficient Deep Convolutional Neural Network Design for Real-Time Facial Expression Recognition
James Ren Lee1, Linda Wang1,2, Alexander Wong1,2
1Vision and Image Processing Lab, Department of Systems Design Engineering, University of Waterloo, Waterloo, ON, Canada.
Frontiers in Artificial Intelligence
|March 18, 2021
Summary
EmotionNet Nano offers efficient facial expression classification (FEC) for real-time embedded systems. This novel deep learning architecture achieves state-of-the-art accuracy with significantly reduced complexity and high energy efficiency.
Failed At:
2026-06-19T13:38:55.517903+00:00
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