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About Facial Expression Recognition Using Weighted Mixture Deep Neural Network Based On Double-Channel Facial Images
The document describes a facial expression recognition system using a weighted mixture deep neural network (WMDNN) that analyzes two channels of facial image data - grayscale images and corresponding local binary pattern (LBP) images. The system first performs preprocessing like face detection and rotation correction. It then extracts expression-related features from each channel using different deep networks, and weights and fuses the outputs to classify six basic facial expressions. Experimental results on three benchmark datasets show the proposed method achieves high recognition accuracy compared to other techniques.
Detailed Information
| Author: | ['Samitha Chathuranga'] |
|---|---|
| Publication Year: | 2019 |
| Pages: | 11 |
| Language: | English |
| Format: | |
| Price: | FREE |
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