Uncertainty Flow Facilitates Zero-Shot Multi-Label Learning in Affective Facial Analysis

Uncertainty Flow Facilitates Zero-Shot Multi-Label Learning in Affective Facial Analysis

Featured Application: The proposed Uncertainty Flow framework may benefit the facial analysis with its promised elevation in discriminability in multi-label affective classification tasks. Moreover, this framework also allows the efficient model training and between tasks knowledge transfer. The app...

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Bibliographic Details
Main Authors: Wenjun Bai, Changqin Quan, Zhiwei Luo
Format: Article
Language:English
Published: MDPI AG 2018-02-01
Series:Applied Sciences
Subjects:
affective computing
Bayesian neural network
Multiple Label Learning
transfer learning
Online Access:http://www.mdpi.com/2076-3417/8/2/300

Internet

http://www.mdpi.com/2076-3417/8/2/300

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