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Kaya ter Burg and Heysem Kaya
Classifying facial expressions is a vital part of developing systems capable of aptly interacting with users. In this field, the use of deep-learning models has become the standard. However, the inner workings of these models are unintelligible, which is...
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Sathya Bursic, Giuseppe Boccignone, Alfio Ferrara, Alessandro D?Amelio and Raffaella Lanzarotti
When automatic facial expression recognition is applied to video sequences of speaking subjects, the recognition accuracy has been noted to be lower than with video sequences of still subjects. This effect known as the speaking effect arises during spont...
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Mei Bie, Huan Xu, Quanle Liu, Yan Gao, Kai Song and Xiangjiu Che
Facial expression recognition (FER) is an important field in computer vision with many practical applications. However, one of the challenges in FER is dealing with small sample data, where the number of samples available for training machine learning al...
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Xiangwei Mou, Yongfu Song, Rijun Wang, Yuanbin Tang and Yu Xin
In the research of Facial Expression Recognition (FER), the inter-class of facial expression data is not evenly distributed, the features extracted by networks are insufficient, and the FER accuracy and speed are relatively low for practical applications...
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Xiuwen Lu, Hongying Zhang, Qi Zhang and Xue Han
Accurate expression interpretation occupies a huge proportion of human-to-human communication. The control of expressions can facilitate more convenient communication between people. Expression recognition technology has also been transformed from relati...
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Danila Germanese, Sara Colantonio, Marco Del Coco, Pierluigi Carcagnì and Marco Leo
Computer vision is a powerful tool for healthcare applications since it can provide objective diagnosis and assessment of pathologies, not depending on clinicians? skills and experiences. It can also help speed-up population screening, reducing health ca...
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Jiaxiong Zhou, Jian Li, Yubo Yan, Lei Wu and Hao Xu
Large-scale facial expression datasets are primarily composed of real-world facial expressions. Expression occlusion and large-angle faces are two important problems affecting the accuracy of expression recognition. Moreover, because facial expression da...
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Hongtao Zhu, Huahu Xu, Xiaojin Ma and Minjie Bian
Facial Expression Recognition (FER) can achieve an understanding of the emotional changes of a specific target group. The relatively small dataset related to facial expression recognition and the lack of a high accuracy of expression recognition are both...
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Changbo Hou, Jiajun Ai, Yun Lin, Chenyang Guan, Jiawen Li and Wenyu Zhu
In 21st-century society, with the rapid development of information technology, the scientific and technological strength of all walks of life is increasing, and the field of education has also begun to introduce high and new technologies gradually. Affec...
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Roberto Pecoraro, Valerio Basile and Viviana Bono
Since the Transformer architecture was introduced in 2017, there has been many attempts to bring the self-attention paradigm in the field of computer vision. In this paper, we propose LHC: Local multi-Head Channel self-attention, a novel self-attention m...
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Huafei Xiao, Wenbo Li, Guanzhong Zeng, Yingzhang Wu, Jiyong Xue, Juncheng Zhang, Chengmou Li and Gang Guo
With the development of intelligent automotive human-machine systems, driver emotion detection and recognition has become an emerging research topic. Facial expression-based emotion recognition approaches have achieved outstanding results on laboratory-c...
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Awais Salman Qazi, Muhammad Shoaib Farooq, Furqan Rustam, Mónica Gracia Villar, Carmen Lili Rodríguez and Imran Ashraf
Facial emotion recognition (FER) is an important and developing topic of research in the field of pattern recognition. The effective application of facial emotion analysis is gaining popularity in surveillance footage, expression analysis, activity recog...
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Yingying Wang, Yibin Li, Yong Song and Xuewen Rong
The convolutional neural network (CNN) has been widely used in image recognition field due to its good performance. This paper proposes a facial expression recognition method based on the CNN model. Regarding the complexity of the hierarchic structure of...
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Yingying Wang, Yibin Li, Yong Song and Xuewen Rong
In recent years, with the development of artificial intelligence and human?computer interaction, more attention has been paid to the recognition and analysis of facial expressions. Despite much great success, there are a lot of unsatisfying problems, bec...
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Yang Lu, Shigang Wang and Wenting Zhao
In this paper, a novel approach to facial expression recognition based on the discrete separable shearlet transform (DSST) and normalized mutual information feature selection is proposed. The approach can be divided into five steps. First, all test and t...
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Yang Lu, Shigang Wang and Wenting Zhao
In this paper, a novel approach to facial expression recognition based on the discrete separable shearlet transform (DSST) and normalized mutual information feature selection is proposed. The approach can be divided into five steps. First, all test and t...
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Yingying Wang, Yibin Li, Yong Song and Xuewen Rong
As an important part of emotion research, facial expression recognition is a necessary requirement in human?machine interface. Generally, a face expression recognition system includes face detection, feature extraction, and feature classification. Althou...
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Thomas Kopalidis, Vassilios Solachidis, Nicholas Vretos and Petros Daras
Recent technological developments have enabled computers to identify and categorize facial expressions to determine a person?s emotional state in an image or a video. This process, called ?Facial Expression Recognition (FER)?, has become one of the most ...
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Ahmed J. Obaid and Hassanain K. Alrammahi
Recognizing facial expressions plays a crucial role in various multimedia applications, such as human?computer interactions and the functioning of autonomous vehicles. This paper introduces a hybrid feature extraction network model to bolster the discrim...
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Reda Belaiche, Yu Liu, Cyrille Migniot, Dominique Ginhac and Fan Yang
Micro-Expression (ME) recognition is a hot topic in computer vision as it presents a gateway to capture and understand daily human emotions. It is nonetheless a challenging problem due to ME typically being transient (lasting less than 200 ms) and subtle...
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