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An Improved Three-Dimensional Model for Emotion Based on Fuzzy Theory
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作者 Zijiang Zhu Junshan Li +1 位作者 xiaoguang deng Yi Hu 《Journal of Computer and Communications》 2018年第8期101-111,共11页
Emotion Model is the basis of facial expression recognition system. The constructed emotional model should not only match facial expressions with emotions, but also reflect the location relationship between different ... Emotion Model is the basis of facial expression recognition system. The constructed emotional model should not only match facial expressions with emotions, but also reflect the location relationship between different emotions. In this way, it is easy to understand the current emotion of an individual through the analysis of the acquired facial expression information. This paper constructs an improved three-dimensional model for emotion based on fuzzy theory, which corresponds to the facial features to emotions based on the basic emotions proposed by Ekman. What’s more, the three-dimensional model for motion is able to divide every emotion into three different groups which can show the positional relationship visually and quantitatively and at the same time determine the degree of emotion based on fuzzy theory. 展开更多
关键词 EMOTION Model FACIAL EXPRESSION FUZZY Theory THREE-DIMENSIONAL STATE-SPACE
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RETRACTED:<i>Realization of Virtual Human Face Based on Deep Convolutional Generative Adversarial Networks</i>
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作者 Zijiang Zhu xiaoguang deng +1 位作者 Junshan Li Eryou Wei 《Journal of Signal and Information Processing》 2018年第3期217-228,共12页
Short Retraction Notice The authors claim that this paper needs modifications. This article has been retracted to straighten the academic record. In making this decision the Editorial Board follows COPE's Retracti... Short Retraction Notice The authors claim that this paper needs modifications. This article has been retracted to straighten the academic record. In making this decision the Editorial Board follows COPE's Retraction Guidelines. The aim is to promote the circulation of scientific research by offering an ideal research publication platform with due consideration of internationally accepted standards on publication ethics. The Editorial Board would like to extend its sincere apologies for any inconvenience this retraction may have caused. Editor guiding this retraction: Prof. Baozong Yuan(EiC of JSIP) The full retraction notice in PDF is preceding the original paper, which is marked "RETRACTED". 展开更多
关键词 DEEP Convolution GENERATIVE Adversarial NETWORKS DEEP Learning Vir-tual Human FACE
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