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About Wild Facial Expression Recognition
This document summarizes a study that used incremental active learning with a convolutional neural network to recognize facial expressions in uncontrolled, or "wild", environments. The researchers collected a large dataset of unlabeled facial images with different expressions and lighting conditions. They trained an incremental active learning framework using a pre-trained VGG16 model to iteratively label more data and improve the model's accuracy. Their method achieved an average 88% accuracy on recognizing seven facial expressions in the wild, outperforming other state-of-the-art approaches.
Detailed Information
| Author: | ['minhaz21'] |
|---|---|
| Publication Year: | 2019 |
| Pages: | 11 |
| Language: | English |
| Format: | |
| Price: | FREE |
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