Tensor-Based Emotional Category Classification via Visual Attention-Based Heterogeneous CNN Feature Fusion

Tensor-Based Emotional Category Classification via Visual Attention-Based Heterogeneous CNN Feature Fusion

The paper proposes a method of visual attention-based emotion classification through eye gaze analysis. Concretely, tensor-based emotional category classification via visual attention-based heterogeneous convolutional neural network (CNN) feature fusion is proposed. Based on the relationship between...

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Bibliographic Details
Main Authors: Yuya Moroto, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama
Format: Article
Language:English
Published: MDPI AG 2020-04-01
Series:Sensors
Subjects:
tensor analysis
visual attention
change with time
feature fusion
convolutional neural network
Online Access:https://www.mdpi.com/1424-8220/20/7/2146

Internet

https://www.mdpi.com/1424-8220/20/7/2146

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