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About High Efficiency Facial Expression Recognition Based Active Semi-Supervised Learning
This document discusses a proposed method for high efficiency adaptive facial expression recognition using active semi-supervised learning (ASSL). The method aims to gather many unlabeled facial expression data and train an initial model using ASSL with a deep learning network to gain high accuracy with less effort. Experimental results on various training data show the proposed method achieves high efficiency. Key aspects of the method include using MTCNN for face detection, modifying the last two layers of VGG for performance, and repeating the ASSL process to improve performance further.
Detailed Information
| Author: | ['minhaz21'] |
|---|---|
| Publication Year: | 2018 |
| Pages: | 9 |
| Language: | English |
| Format: | |
| Price: | FREE |
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