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Adaptively Enhancing Facial Expression Crucial Regions via a Local Non-local Joint Network
Facial expression recognition (FER) is still challenging due to the small interclass discrepancy in facial expression data. In view of the...
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Cross-view adaptive graph attention network for dynamic facial expression recognition
Dynamic facial expression recognition is important for human–computer interaction. Learning the temporal dynamic representation of facial expressions...
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Three-phases hybrid feature selection for facial expression recognition
Machine learning applications are increasingly challenged by the growing volume of data. In this context, selecting relevant features from the vast...
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Local-Global Cross-Fusion Transformer Network for Facial Expression Recognition
Facial Expression Recognition (FER) has received increasing attention in the computer vision community. For FER, there are two challenging issues...
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Counterfactual Fairness for Facial Expression Recognition
Given the increasing prevalence of facial analysis technology, the problem of bias in these tools is becoming an even greater source of concern....
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Neural style transfer generative adversarial network (NST-GAN) for facial expression recognition
With the increasing number of intelligent human–computer systems, more and more research is focusing on human emotion recognition. Facial expressions...
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OpenFE: feature-extended OpenMax for open set facial expression recognition
Open-set methods are crucial for rejecting unknown facial expressions in real-world scenarios. Traditional open-set methods primarily rely on a...
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Improved ConvNeXt Facial Expression Recognition Embedded with Attention Mechanism
Facial expression recognition (FER) is an emerging and important research field in the field of pattern recognition, with wide applications in safe...
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Learning facial expression-aware global-to-local representation for robust action unit detection
The task of detecting facial action units (AU) often utilizes discrete expression categories, such as Angry, Disgust, and Happy, as auxiliary...
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A lightweight facial expression recognition model for automated engagement detection
Real-time monitoring of students’ classroom engagement level is of paramount importance in modern education. Facial expression recognition has been...
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A facial expression recognition algorithm incorporating SVM and explainable residual neural network
To address the problem that traditional convolutional neural networks cannot classify facial expression image features precisely, an interpretable...
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Facial expression intensity estimation using label-distribution-learning-enhanced ordinal regression
Facial expression intensity estimation has promising applications in health care and affective computing, such as monitoring patients’ pain feelings....
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Enhancing facial geometry analysis by DeepFaceLandmark leveraging ResNet101 and transfer learning
The face recognition is the pivotal component in the surveillance system. To comprehensively assess facial structures, acquiring facial features...
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CenterMatch: A Center Matching Method for Semi-supervised Facial Expression Recognition
The label uncertainty in large-scale qualitative facial expression datasets, caused by low-quality images and subjective annotations, combined with...
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Cephalometry analysis of facial soft tissue based on two orthogonal views applicable for facial plastic surgeries
Cephalometry analysis of facial soft tissue plays an important role for anthropologists in facial plastic surgeries. There are two important problems...
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Facial Expression Recognition Using Machine Learning and Deep Learning Techniques: A Systematic Review
In the contemporary era, Facial Expression Recognition (FER) plays a pivotal role in numerous fields due to its vast application areas, such as...
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A Method of Students’ Online Learning Status Analysis Based on Facial Expression
In order to monitor students’ emotional status during online learning, we propose a method to analyze students' online learning status by sentiment...
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Towards Facial Expression Robustness in Multi-scale Wild Environments
Facial expressions are dynamic processes that evolve over temporal segments, including onset, apex, offset, and neutral. However, previous works on...
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Ethical AI in facial expression analysis: racial bias
Facial expression recognition using deep neural networks has become very popular due to their successful performances. However, the datasets used...
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Optimizing facial feature extraction and localization using YOLOv5: An empirical analysis of backbone architectures with data augmentation for precise facial region detection
The task of object detection in computer vision revolves around the identification of objects within images or videos. A specific subtask within...
