Optimizing Class Imbalance in Facial Expression Recognition Using Dynamic Intra-Class Clustering

Optimizing Class Imbalance in Facial Expression Recognition Using Dynamic Intra-Class Clustering

While deep neural networks demonstrate robust performance in visual tasks, the long-tail distribution of real-world data leads to significant recognition accuracy degradation in critical scenarios such as medical human–robot affective interaction, particularly the misidentification of low-frequency...

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Bibliographic Details
Main Authors: Qingdu Li, Keting Fu, Jian Liu, Yishan Li, Qinze Ren, Kang Xu, Junxiu Fu, Na Liu, Ye Yuan
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Biomimetics
Subjects:
facial expression recognition
class imbalance
dynamic intra-class clustering algorithm
deep learning
Online Access:https://www.mdpi.com/2313-7673/10/5/296
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